Challenges and strategies for the identification and correction of patient–ventilator asynchronies in daily practice: a scoping review

Abstract

Patient–ventilator asynchronies (PVA) are associated with adverse clinical outcomes, including prolonged ventilatory support and increased mortality both in the intensive care unit (ICU) and at the hospital level. Despite their clinical relevance, the detection and management of PVA remain challenging in daily practice because of multiple factors, such as the lack of continuous monitoring and the low recognition by healthcare professionals. The aim of this review is to map and synthesize the available evidence on the main challenges in the identification and management of PVA and to describe the strategies proposed to overcome them. We conducted a scoping review following Joanna Briggs Institute guidance and reported in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR). PubMed/Medline, Scopus, ScienceDirect, LILACS, and the Cochrane Library were searched from inception to April 2025. Two reviewers independently screened records and selected eligible studies. Data were charted using a standardized extraction form, and findings were synthesized descriptively. The identified challenges were categorized into three main groups, and the proposed strategies were classified according to the type of challenge addressed. The scoping review included 33 studies published between 2000 and 2025. Of these, 18 provided explanatory evidence, whereas 16 described strategies for addressing challenges in daily clinical practice. Overall, this scoping review identified 15 distinct challenges. This review highlights the multifaceted challenges affecting the recognition and management of PVA in adult ICU patients. By mapping challenges across clinical, structural, and cultural domains and summarizing strategies to address them, this review provides professionals with a practical framework to improve patient–ventilator interaction.

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INTRODUCTION

Patient–ventilator asynchronies (PVA) are defined as a mismatch between the mechanical and the neural inspiratory time, or, more broadly, as a mismatch between ventilator's assistance and the patient’s ventilatory demands [1]. These asynchronies are commonly observed in patients admitted to the intensive care unit (ICU) [2], with reported incidence rates ranging from 25% to 93% among mechanically ventilated (MV) patients [3,4]. The presence of PVA has been associated with adverse clinical outcomes, including prolonged duration of MV and increased mortality rates both in the ICU and at the hospital level [5,6]. While PVA have traditionally been regarded as harmful, emerging evidence calls for a reassessment of this perspective: not all asynchronies appear to be inherently detrimental. On the contrary, it is essential to adopt a strategic approach that distinguishes which types are truly deleterious and which may be neutral or even potentially beneficial in specific clinical contexts [7].

Despite its clinical significance, timely and accurate identification of PVA remains a challenge in routine clinical practice. Several factors may hinder this process, such as the limited ability to recognize PVA, the lack of specific alarms for their detection, and the inability to monitor continuously ventilatory waveforms [8,9]. However, a review of the challenges in addressing PVA has not been reported. A better understanding of these aspects would offer intensive care professionals and managers a practical and accessible resource to enhance the quality of care for MV patients. Therefore, the aim of this scoping review is to synthesize the existing evidence regarding the challenges in addressing PVA and to describe the available strategies to manage and overcome these challenges.

MATERIALS AND METHODS

Given the nature of this study, ethical approval was not required, as it did not involve human participants or the collection of primary data.

This scoping review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist [10] and followed the methodological guidance of the Joanna Briggs Institute (JBI). The review process comprised the following stages: (1) formulation of the research question, (2) identification of relevant evidence, (3) study selection, (4) data extraction, (5) synthesis and presentation of the results, and (6) interpretation of findings and conclusions.

Research Question

This scoping review was guided by the Population, Concept, and Context (PCC) framework, in accordance with JBI guidance. Population (P): adult patients (≥18 years) admitted to the ICU and receiving invasive MV; Concept (C): challenges, barriers, and strategies related to the identification, monitoring, prevention, and management of PVA, including educational/training approaches and clinical or technological interventions aimed at improving PVA recognition and clinical response; Context (C): hospital critical care settings, including general ICUs and specialized ICUs (e.g., medical, surgical, neurocritical care, and cardiothoracic ICUs).

Eligibility Criteria

The literature search was conducted in accordance with the review question. We included studies addressing PVA in adult ICU patients receiving invasive MV, with a particular focus on challenges, barriers, and strategies related to PVA recognition, monitoring, prevention, and management. Eligible evidence sources included randomized controlled trials, descriptive or analytical observational studies, qualitative research, clinical guidelines or consensus documents, and systematic or narrative reviews, provided they contributed relevant information to the scope of this review. Given the objective of mapping the breadth of available evidence, an inclusive approach consistent with JBI methodological guidance for scoping reviews was adopted. No restrictions were applied regarding year of publication, and studies published in English, Spanish, or Portuguese were considered eligible. Two independent reviewers (AMEP, HMPG) screened titles and abstracts and assessed full texts for eligibility. Disagreements were resolved through discussion and consensus or, when necessary, by consultation with a third reviewer.

Exclusion Criteria

Studies not involving adult patients (≥18 years) receiving invasive MV in an ICU setting were excluded. Evidence focused exclusively on non-invasive ventilation, pediatric populations, or non-critical care environments was also excluded. Additionally, studies were excluded if they did not address PVA or did not provide relevant information on challenges, barriers, or strategies related to PVA recognition, monitoring, prevention, or management. Conference abstracts without full-text availability, editorials, letters to the editor, and expert opinions lacking sufficient methodological detail or empirical evidence to support data charting were also excluded.

Information Sources

A comprehensive literature search was conducted across five electronic databases—PubMed/Medline, Scopus, ScienceDirect, LILACS, and the Cochrane Library—from database inception to April 2025. The search strategy combined controlled vocabulary (Medical Subject Headings [MeSH] in PubMed/Medline and Descriptores en Ciencias de la Salud [DeCS] in LILACS) with free-text terms.

The main controlled terms included “Respiration, Artificial” [MeSH], “Intensive Care Units” [MeSH], and “Critical Care” [MeSH], combined with keywords related to patient–ventilator asynchronies (e.g., “patient–ventilator asynchronies”, “patient–ventilator dyssynchronies”, “asynchron”, “dyssynchron”). In addition, the reference lists of all included studies were manually screened to identify further eligible evidence. The complete search strategies for each database are provided in Supplementary Material 1.

Search Strategy

The research question was formulated using the PCC framework, in accordance with JBI guidance for scoping reviews. The search strategy combined controlled vocabulary (Medical Subject Headings [MeSH] and Descriptores en Ciencias de la Salud [DeCS]) with free-text terms in English, Spanish, and Portuguese, focusing on PVA and evidence describing challenges, barriers, and strategies related to its recognition, monitoring, prevention, and management in adult ICU patients receiving invasive MV.

Database-specific search strategies were developed and iteratively refined by the review team to maximize sensitivity and coverage, adapting the syntax and indexing features of each platform. Duplicate records were removed prior to screening. Study selection was conducted using Rayyan [11] (Rayyan Systems Inc.) to enable blinded and independent screening by two reviewers. Disagreements were resolved through discussion and consensus or, when necessary, by consultation with a third reviewer. Screening was performed in two stages (title/abstract screening followed by full-text assessment) according to predefined eligibility criteria. Studies meeting all inclusion criteria were included in the data charting and synthesis.

Data Synthesis and Extraction

Data were charted using a standardized extraction form developed a priori. The data charting process was conducted iteratively and refined as needed during the review process. Extracted items included author/year, type of evidence source or study design, and three predefined domains: (1) challenges, (2) explanations/rationale, and (3) proposed strategies related to PVA.

Charting was conducted in two stages: an initial evidence mapping table (with presence marked as “X”), followed by a detailed charting table to expand and synthesize domain-specific information. Extracted data were summarized in structured evidence tables and synthesized narratively to identify key gaps, including limited evidence on implementation strategies, education and training approaches, and ICU-related barriers (e.g., unit culture, workflow, communication, and monitoring resources).

To facilitate the translation of findings into clinical practice, the identified challenges were organized into three main categories, enhancing both their interpretation and applicability in critical care settings: (1) Challenges in specific clinical scenarios: clinical conditions and patient characteristics associated with a higher risk of PVA or difficulties in recognizing and correcting these events; (2) ICU structural challenges: organizational and resource-related barriers within the ICU setting; (3) ICU cultural challenges: factors related to the prevailing culture within the ICU that may influence the recognition and management of PVA, beyond physical and technical resources.

Proposed strategies were categorized according to the type of challenges they aimed to address. A formal critical appraisal of the included studies was not performed, as the aim of this scoping review was to map the available evidence rather than to assess the methodological quality of individual studies, in accordance with JBI guidance.

RESULTS

In the initial search, 2,109 records were retrieved from five databases. After removing 2,009 duplicate records, 100 records underwent title and abstract screening, of which 60 were excluded. Forty full-text articles were assessed for eligibility, of which seven were excluded. Finally, 33 studies were included in the scoping review (Figure 1).

Figure 1.

Study selection flowchart.

Characteristics of the Included Studies

The included studies [8,9,12-42] were published between 2000 and 2025, reflecting sustained and progressively increasing scientific interest in the field, with a notable rise in research output in recent years, particularly in 2025. In terms of study design, narrative reviews predominated [12,18-22,27,33,34,39,40,42], underscoring ongoing efforts to synthesize and consolidate existing evidence. These were followed by prospective observational studies [13,15,31,37], including cohort designs [36].

The overall methodological landscape was heterogeneous, encompassing cross-sectional observational studies [8,9], systematic reviews [23,29], qualitative and descriptive observational studies [28,32,41], and quasi-experimental designs [24,38]. Additional approaches included modeling and simulation studies [35], algorithm validation studies [26], pilot and experimental observational studies [17,25], retrospective observational studies [30], crossover clinical trials [14], and case reports [16] (Table 1).

Table 1.

Characteristics of the included studies

Study	Year	Type of study	Justification
			Explanation	Strategy
Ramírez et al. [8]	2021	Cross-sectional observational	×
Enríquez Popayán et al. [9]	2025	Cross-sectional observational	×
Ghamloush et al. [12]	2011	Narrative review	×
de Wit et al. [13]	2009	Prospective observational	×
Alexopoulou et al. [14]	2013	Crossover clinical trial		×
Luo et al. [15]	2020	Prospective observational	×
Saga et al. [16]	2025	Case report	×	×
Imanaka et al. [17]	2000	Observational experimental	×
Saavedra et al. [18]	2022	Narrative review		×
Mellott et al. [19]	2009	Narrative review	×
López-Aguilar et al. [20]	2013	Narrative review	×
Spinelli et al. [21]	2020	Narrative review	×
Costa et al. [22]	2025	Narrative review	×
Sontakke et al. [23]	2023	Systematic review		×
Ramírez et al. [24]	2024	Prospective quasi-experimental		×
Blanch et al. [25]	2012	Pilot observational		×
Bakkes et al. [26]	2023	Algorithm validation		×
Longhini et al. [27]	2023	Narrative review	×
Wisse et al. [28]	2024	Qualitative observational		×
Rae et al. [29]	2021	Systematic review	×
Twigg et al. [30]	2013	Retrospective observational		×
Thille et al. [31]	2006	Prospective observational	×
Yujen et al. [32]	2022	Descriptive observational		×
Holanda et al. [33]	2018	Narrative review	×
Bulleri et al. [34]	2018	Narrative review	×
Tanchuco et al. [35]	2025	Modeling/simulation		×
Bloos et al. [36]	2009	Prospective cohort		×
Colombo et al. [37]	2011	Prospective observational	×
Lynch-Smith et al. [38]	2016	Quasi-experimental		×
Nilsestuen et al. [39]	2005	Narrative review		×
de Haro et al. [40]	2019	Narrative review		×
Reader et al. [41]	2007	Qualitative observational	×
Leonard et al. [42]	2004	Narrative review		×

Challenges and strategies

A total of 15 challenges related to PVA were identified and grouped into three major domains. Each challenge was accompanied by one or more mitigation strategies.

Within the domain of specific clinical scenarios, five challenges were identified. Delirium and agitation were associated with the highest number of reported strategies (n=6), whereas artificial airway dysfunction had the fewest (n=3). Across this domain, the most frequently reported strategy was regular monitoring and early identification of patients at risk, consistently described across several challenges (Table 2).

Table 2.

Challenges and strategies related to specific clinical scenarios

Challenge	Explanation	Strategy
Delirium/agitation	Delirium and agitation increase respiratory drive, whereas their pharmacological management may excessively suppress it; moreover, prolonged sedation is associated with a higher risk of delirium [12,13].	· Avoid prolonged sedation
		· Pharmacological delirium prevention
		· Non-pharmacological delirium prevention
		· Assisted ventilation modes
		· High-risk patient monitoring
		· Recognize high respiratory drive (not under-assistance) [14]
Acute brain injury	Patients with acute brain injury often have impaired respiratory control, high respiratory drive, and irregular breathing patterns that promote asynchronies [15].	· Identify high-risk patients
		· Address pathophysiology
		· Frequent monitoring
		· Control high respiratory drive (if indicated)
		· Individualized ventilator settings
		· Dynamic reassessment and adjustment [16]
Hemodynamic instability, small time constant of the respiratory system	Patients with low respiratory drive and short time constants are prone to auto-triggering [17], as cardiac oscillations may trigger the ventilator, allowing assisted ventilation without patient inspiratory effort.	· Identify at-risk patients
		· Monitor for auto-triggering frequently
		· Avoid excessive sedation and address low respiratory drive
		· Adjust trigger sensitivity cautiously
		· Differentiate cardiac oscillations from true patient efforts
		· Determine patient-triggered versus ventilator-triggered breaths [18]
Altered respiratory drive due to metabolic acidosis or alkalosis	Metabolic acidosis increases respiratory drive through central chemoreceptor stimulation, whereas alkalosis suppresses it by inhibiting respiratory centers, leading to distinct PVA patterns and highlighting the role of brain–lung interactions in MV [19,21].	· Identify at-risk patients
		· Manage underlying metabolic disorders
		· Adjust ventilator parameters according to clinical needs
		· Prioritize lung-protective ventilation [16]
Dysfunction of the artificial airway	Secretions or water in artificial airways can cause multiple asynchronies, including auto-triggering and those related to increased airway resistance [16,22].	· Clear endotracheal and tracheostomy tubes
		· Remove airway secretions
		· Ensure unobstructed airflow delivery [23]

PVA: patient–ventilator asynchronies; MV: mechanical ventilation.

Within the domain of ICU structure, seven challenges were identified. Lack of advanced monitoring was associated with the highest number of strategies (n=4), whereas limited monitoring of ventilator waveforms was linked to the fewest (n=1). Across this domain, the most commonly reported strategy was continuous staff training and education, consistently described across multiple challenges (Table 3).

Table 3.

Challenges and strategies related to the internal structure of the intensive care unit

Challenge	Explanation	Strategy
Inadequate staff training	Limited training in MV hinders effective PVA prevention and management, as poor waveform interpretation skills increase the risk of undetected or uncorrected asynchronies [8].	· Develop targeted educational strategies
		· Implement continuous PVA training for ventilatory support personnel [24]
Lack of frequent monitoring of ventilator waveforms	In daily clinical practice, it is nearly impossible for healthcare professionals to continuously monitor ventilator waveforms 24 hours a day [9].	· Implement specialized software for asynchrony detection [25,26]
Lack of advanced monitoring	Advanced monitoring, such as esophageal and gastric pressure measurement, enables timely detection of asynchronies in complex cases and may reduce adverse clinical outcomes [27].	· Deploy advanced monitoring technologies
		· Use ventilators with esophageal pressure monitoring
		· Conduct cost–benefit and economic impact analyses
		·Train staff in equipment use [18,28]
Limited support staff	A higher number of healthcare professionals would allow more frequent and detailed monitoring of ventilator waveforms, potentially reducing adverse clinical outcomes [29].	· Evaluate additional ICU staffing needs
		· Perform financial modeling
		· Assess the economic benefits of increased staffing levels [30]
Discomfort associated with specific errors in the inappropriate setting of ventilatory parameters	Inadequate ventilator settings can induce the occurrence of asynchronies [31].	· Regularly reassess patients
		· Monitor ventilator waveforms
		· Adjust ventilator parameters according to patient condition and clinical goals [32]
Inadequate programming of ventilatory alarms	Suboptimal alarm configuration (inappropriate thresholds, excessive alarm load, or poor alarm response protocols) may delay the recognition of clinically relevant events, contributing to missed asynchrony detection and delayed corrective interventions [33].	· Regularly reassess and individualize alarm settings based on clinical goals and ventilator configuration [32]
Lack of ventilators with graphical monitoring capabilities	Although most mechanical ventilators provide waveform monitoring, its absence in some institutions hinders the detection of PVA [34].	· Implement new ventilators
		· Conduct financial cost analyses
		· Assess economic benefits
		· Train staff in equipment use [24,35,36]

MV: mechanical ventilation; PVA: patient–ventilator asynchronies; ICU: intensive care unit.

Within the ICU culture domain, three challenges were identified. The use of sedation to manage ventilator asynchronies was associated with the highest number of strategies (n=5), whereas underestimation of the clinical relevance and associated adverse events had the fewest (n=2). Notably, no single strategy was consistently reported across all challenges in this domain (Table 4). The 15 challenges and their corresponding mitigation strategies are detailed in Tables 2–4 and summarized in Figure 2.

Table 4.

Challenges and strategies related to the culture of the intensive care unit

Challenge	Explanation	Strategy
Underestimation of the clinical relevance and the adverse events associated with its presence	A low proportion of professionals recognize PVA in real time, indicating underestimation of both the presence and clinical impact of asynchronies [37].	· Provide interprofessional education
		· Train staff on the clinical impact of PVA [38]
Use of sedation to manage ventilator asynchronies	Sedation is sometimes inappropriately used to manage asynchronies [13].	· Monitor ventilator waveforms
		· Identify PVA
		· Adjust ventilator settings according to patient condition
		· Regularly reassess the patient
		· Consider sedation only after confirming asynchrony and exhausting non-sedation alternatives [39,40]
Lack of communication among healthcare professionals	Lack of assertive communication among healthcare professionals can lead to misaligned goals and inconsistent treatment plans [41].	· Implement structured interdisciplinary meetings
		· Standardize communication protocols
		· Promote coordination and alignment of therapeutic goals [42]

PVA: patient–ventilator asynchronies.

Figure 2.

Challenges in the identification and management of patient–ventilator asynchronies.

DISCUSSION

In this scoping review, we identified 15 key challenges related to PVA and the strategies proposed to address them. Importantly, many of these challenges are not solely related to technology availability or ventilator waveform monitoring, but are strongly influenced by the patient’s clinical condition and underlying pathophysiology. Regarding challenges within specific clinical scenarios, we found that asynchronies do not always originate from the ventilator itself; rather, they may be driven by clinical factors that predispose patients to their occurrence. These factors can be broadly classified as modifiable and non-modifiable. Modifiable factors, particularly those related to the artificial airway, can often be addressed promptly, which may contribute to reducing PVA. For instance, Cortés-Telles et al. [43] highlighted secretion removal through artificial airway suctioning as an effective and widely available strategy across ICUs.

In contrast, managing non-modifiable factors is inherently more complex, as conditions such as delirium, brain injury, or metabolic disturbances may lead to diverse asynchrony patterns. Nevertheless, minimizing PVA ultimately requires addressing their underlying causes, which frequently reflect patient-specific clinical and pathophysiological mechanisms. Zhang et al. [44] noted that sedation tailored to the patient’s clinical profile may reduce delirium risk and other associated complications. Therefore, these findings suggest that personalized management may be particularly important, especially in patients with higher risk profiles. Importantly, ventilator adjustments should primarily aim to minimize asynchrony while maintaining lung-protective ventilation. These adjustments should not be expected to fully address the underlying cause of asynchrony, which frequently reflects patient-specific clinical and pathophysiological factors.

Concerning the internal structure of the ICU, challenges are largely related to resource constraints. Although acquiring advanced monitoring capabilities often requires institutional investment, available cost–benefit analyses suggest that such investments may be economically justified. Liu et al. [45] reported that none of the assessed professionals were able to identify the eight asynchronies evaluated, whereas a remote monitoring platform detected all events. Similarly, Enríquez Popayán et al. [9] indicated that most professionals do not perform continuous monitoring of ventilator waveforms, and Kyo et al. [5] demonstrated that the presence of PVA is a statistically significant factor associated with adverse clinical outcomes.

Therefore, the implementation of specialized monitoring may contribute to reducing the occurrence of asynchrony patterns and could indirectly shorten the duration of MV, ultimately decreasing healthcare costs. This supports the need for dedicated software tools for asynchrony detection in ICU settings, not only due to their potential economic impact but also because of their capacity to mitigate ventilator-associated complications [46,47].

Despite the increasing number of studies using automated tools to detect asynchronies, expert bedside assessment remains highly important and should complement automated tools. Ultimately, the effective integration of advanced technology with clinical judgment will be key to addressing these challenges. However, until such tools become widely available across ICUs, the judgment and expertise of healthcare professionals responsible for ventilatory support will remain crucial for the accurate identification of asynchronies. Consequently, it is essential that healthcare professionals receive specific training in this area. International studies have consistently shown that clinicians often demonstrate limited ability to recognize these events [48], whereas targeted educational interventions can significantly improve detection competence [24]. Training may be further strengthened through the use of mnemonics linked to specific asynchrony patterns, which may facilitate the integration of these concepts into routine bedside practice [49].

Regarding monitoring equipment, esophageal pressure measurement is widely regarded as the gold standard for detecting and interpreting asynchronies due to its high accuracy. However, its implementation remains limited in most ICUs. Moreover, asynchrony patterns identified using esophageal pressure may differ from those detected through conventional ventilator waveform analysis, adding complexity to bedside interpretation. In this context, more accessible and less invasive approaches such as automated artificial intelligence–based systems may represent a promising alternative for early, continuous, real-time detection of asynchronies.

A major challenge in daily ICU practice is the limited routine monitoring of ventilator waveforms. This gap may be partially explained by the high clinical workload, which can hinder healthcare professionals from completing required tasks and reduce the feasibility of continuous bedside waveform observation [50]. One potential strategy to reduce the occurrence of asynchronies is the implementation of structured monitoring protocols. For example, See et al. [51] reported that a program involving waveform assessment at least twice daily was associated with reduced hospital mortality. These outcomes could be further strengthened by optimizing the healthcare professional-to-patient ratio [52], as improved staffing levels may facilitate protocol adherence and ensure that essential responsibilities related to ventilatory support are consistently met.

Regarding ICU culture-related challenges, these are largely shaped by healthcare professionals’ perceptions and attitudes. Although changing an established culture is inherently complex, Haniffa et al. [53] showed that a structured training program focused on core ICU practices can positively influence institutional performance indicators. This supports the idea that continuous education initiatives may promote gradual and sustained improvements in team members’ perceptions, ultimately facilitating the uptake of new clinical practices that enhance patient outcomes and quality metrics. Additionally, inadequate team communication may contribute to delayed recognition and correction of asynchrony events, highlighting the need for structured interdisciplinary communication and shared decision-making during ventilatory support.

Such a program should prioritize healthcare professionals directly involved in ventilatory support, as they typically already possess the theoretical foundation of ventilator operation and settings, and may therefore benefit most from targeted, competency-based training in asynchrony recognition and management. In patients receiving MV, the use of sedative and analgesic medications is common [54,55]. However, using sedation as a primary strategy to correct asynchronies may not always be appropriate. Evidence suggests that patients requiring frequent or high-dose sedation often have poorer clinical outcomes [56]. Therefore, an early priority should be to identify the specific asynchrony pattern and implement appropriate ventilator adjustments. Sedation and analgesia may be best reserved as a last-line approach in selected complex situations, such as severe psychomotor agitation. Although such episodes are unlikely to be triggered by the ventilator itself, increased respiratory effort combined with intense patient movement may precipitate asynchronies.

While several comprehensive reviews have explored this field, our work offers a different and complementary perspective. Existing reviews largely focus on the recognition and management of individual asynchrony types; in contrast, we propose a framework that targets the underlying causes of PVA, organized into three overarching domains. The main contribution of this review is to provide clinicians with a structured and simplified overview of key barriers, enabling them to identify those present within their own clinical setting and consider context-specific solutions to reduce the occurrence of asynchronies. This framework may be useful for both current and future ICU professionals involved in ventilatory support.

We acknowledge that some proposed strategies are supported by limited or indirect evidence; in these cases, recommendations should be interpreted as complementary approaches derived from the authors’ proposals and the best available evidence. Importantly, this review provides a foundation for future research. Future studies should aim to evaluate the clinical and organizational impact of implementing these strategies, including potential effects on patient outcomes, ventilator-associated complications, and healthcare resource utilization.

A wide range of challenges can hinder the identification and correction of patient–ventilator asynchronies. This scoping review synthesized the available evidence and identified 15 key challenges, along with strategies proposed to mitigate them. However, implementing all strategies simultaneously may be difficult and requires an integrated, multidisciplinary approach that combines technological tools with continuous professional development and context-specific adaptation. Further studies are needed to evaluate the clinical and organizational impact of implementing each strategy, particularly regarding patient outcomes and institutional quality indicators. Ultimately, reducing asynchrony events requires identifying the specific barriers within each institution and addressing them progressively through targeted and sustainable interventions.

KEY MESSAGES

▪ Understanding patient–ventilator interaction goes beyond waveform interpretation; multiple clinical, technical, and organizational challenges amplify this complex relationship.

▪ Patient–ventilator asynchronies are frequently overlooked, and underestimating their clinical relevance can aggravate complications and worsen outcomes.

▪ Integrating advanced monitoring technologies with professional expertise will be key to optimizing patient–ventilator interaction and improving critical care outcomes.

SUPPLEMENTARY MATERIALS

Supplementary materials can be found via https://doi.org/10.4266/acc.006050.