Real-time ventilation quality feedback devices efficacy in out-of-hospital cardiac arrest: a scoping review

Abstract

Background

New devices are now available to provide real-time feedback on ventilation for basic life support providers responding to out-of-hospital cardiac arrest (OHCA). This scoping review, conducted as part of the evidence review for the International Liaison Committee on Resuscitation, aimed to examine the extent of evidence examining ventilation feedback devices and to identify research gaps regarding these devices.

Methods

This scoping review was conducted using Arksey and O’Malley’s framework and reported according to PRISMA-ScR guidelines. Medline, EMBASE and Cochrane were searched from database inception to March 13th, 2025. Studies examining real-time ventilation quality feedback in humans and manikins of any design were included. Ventilation feedback devices were defined as any device that can provide information on the delivery of each insufflation (including insufflation and/or exsufflation measured volume as well as rate) and to guide the ventilation through real-time feedback.

Results

We screened 794 titles, with 17 studies (including 4 conference abstracts) included: one randomised trial (RCT), one before-after prospective studies, two observational studies, one case series and 12 simulation studies. Only three simulation studies assessed a pediatric scenario. The RCT reported improved early outcomes (unadjusted return of spontaneous circulation and 30-hour survival) with real-time feedback, but no difference at hospital discharge. Two observational studies also found no change in patient outcomes, but noted improved ventilation rate and insufflation volumes. Most simulation studies showed improvements in ventilation parameters.

Conclusion

Real-time feedback devices seem to improve ventilations, but we found insufficient evidence of their effect on clinical outcomes to merit a systematic review at this time. Rigorous evaluation of the clinical efficacy and effectiveness of these devices is needed.

Introduction

High-quality cardiopulmonary resuscitation (CPR) includes chest compression and positive pressure ventilations. Real-time CPR feedback has been studied as a potential method to improve the quality of CPR and patient outcomes.¹ While several feedback devices have been studied and validated to improve chest compression during CPR, the quality of ventilation during CPR has not had the same attention, and most of the real-time CPR feedback devices focus only on ventilation rate.2, 3

Current guidelines recommend ventilating adult patients in cardiac arrest at a rate of 8–12 per minute and a tidal volume (Vt) of 500–600 ml,4, 5 and for children to adjust respiratory rate (and expiratory time) and/or tidal volume [TV] according to age.⁶ Recently, inadequate ventilation delivery was observed in more than 60 % of pauses during 30:2 CPR in adult out-of hospital cardiac arrest (OHCA) patients, and this was associated with a decrease in return of spontaneous circulation (ROSC), survival and favourable neurologic outcome.⁷ Recently, feedback devices have been developed to monitor and provide real-time feedback on ventilation during CPR.8, 9, 10 To our knowledge, these new devices have not been systematically assessed, and their impact on ventilation quality during CPR is unknown.

To address this gap, on behalf of the International Liaison Committee on Resuscitation (ILCOR) Basic Life Support Task Force, a scoping review was chosen to examine the extent of evidence examining ventilation feedback devices broadly and to identify research gaps. The following research question was formulated: In adults and children who are in cardiac arrest in any setting (P), does the use of real-time ventilation quality feedback (I) (e.g. tidal volume, adequate ventilation, mask leak, ventilation rate) compare to no feedback (C) improve ventilation and patient outcomes (O)?

Methods

A formal written protocol was created by the scoping review study team (see Supplementary Material). The finalized protocol was approved by the ILCOR BLS Task Force and the ILCOR Scientific Advisory Committee (SAC) prior to the execution of the search strategy. Conflicts of interest were managed in accordance with ILCOR guidelines; where a reviewer was an author of an included paper, the decision to include that study and data extraction was undertaken by other members of the review group. This review followed ILCOR processes and the Arksey and O’Malley’s methodological steps for scoping reviews, with the refinements proposed by Levac.11, 12 This review is reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR).¹³

Eligibility criteria

Table 1 describes the eligibility criteria for selecting appropriate articles for this review. The population was adults and children with OHCA or in-hospital cardiac arrest (IHCA) with use of real-time ventilation quality feedback. All outcomes were accepted, although the following outcomes were defined a priori as the most relevant for the research question: survival with favorable neurologic outcome at discharge, 30 days or longer, survival to hospital discharge, return of spontaneous circulation, oxygenation (measured via pulse oximetry or blood gas), blood gas parameters (e.g., pH, partial pressure of carbon dioxide [PCO2], partial pressure of oxygen [PO2]), tidal volume or measured expiratory volume, adherence to guideline-recommended ventilation rates and tidal volumes, mask leaks. Since we expected a lack of evidence, we decided a priori to include studies with no control group to capture and describe all available evidence on this subject. Simulation and cadaver studies assessing ventilation using ventilation quality feedback devices were included. Publications in any language were included if an English abstract was available. Studies were excluded if they: included devices with only prompts to help guide ventilation rates (metronome, flashing lights); related to devices that need an advanced airway (e.g. endotracheal tube, supraglottic airway) and/or design to actively improve the performance of ventilation (mechanical ventilators, devices design to improve circulation); or, included only ventilation feedback built into a training manikin or audio/visual feedback provided by an instructor.

Table 1.

Summary of PICOST and predefined inclusion criteria for selecting articles.

Population	In adults and children in out-of-hospital cardiac arrest
Intervention	Real-time ventilation quality feedback (e.g. tidal volume, adequate ventilation, mask leak, ventilation rate).
Comparison	No real-time ventilation feedback
Outcomes	Any outcome with a preference for outcomes listed in the ILCOR Core Outcome Set for Cardiac Arrest (COSCA)35 or Pediatric-COSCA.36
Study Design	Randomized controlled trials (RCTs) and non-randomized studies (non-randomized controlled trials, interrupted time series, controlled before-and-after studies, cohort studies), simulation studies, case series, and case reports are eligible for inclusion. Grey literature (Google Scholar − first 20 pages), letters to the Editor and conference abstracts were also eligible for inclusion.
Timeframe	Inception to March 13th, 2025

Information sources and search strategy

The search strategy was developed with assistance from an information specialist. Key search terms and the search strategy are provided in Supplementary Materials. After review from the ILCOR BLS Task Force, the search strategy was run on September 11th, 2024 and updated on March 13th, 2025. Articles for review were obtained through Ovid MEDLINE(R), EMBASE and the Cochrane Database of Systematic Reviews and the Cochrane Central Register of Controlled Trials. Grey literature (Google Scholar − first 20 pages), letters to the Editor and conference abstracts were also searched and eligible for inclusion.

Selection Process

All citations were uploaded into Covidence^TM for screening and duplicates were removed.

Two authors (GD, NJ, MD, JB) reviewed independently each title and abstract against inclusion and exclusion criteria. For initial screening, limited exclusion criteria were employed to have broader inclusion. After initial screening, all potentially eligible full texts were retrieved and further reviewed by three authors (GD, NJ, MD) against the same eligibility criteria. Additional citations were searched through hand search of the reference list of included studies following the initial review. Whenever there was uncertainty about a potentially eligible study, the final decisions were achieved by discussion and consensus.

Data extraction and charting the data

Data were abstracted using a form available on Covidence.¹⁴ The primary author extracted the data using standardised data abstraction forms and all data were checked for accuracy by co-authors. All discrepancies between reviewers at each stage were resolved by discussion between co-authors. The following information was extracted for each included study: year and origin of publication, study design, population, participant, number of included patients, intervention, comparator, outcomes, limitations and main findings if reported.

Synthesis of results

Given the variation in study design, populations, and outcomes, the synthesis approach was Arskey and O’Mally framework for summarizing and reporting the results11, 12 and narrative synthesis methods.¹⁵ Interpretation of the synthesis was by discussion within the research team and resuscitation science experts from the BLS ILCOR Task Force.¹⁶ The studies were thought to be too heterogenous to consider critical appraisal.¹⁷

Results

In our search of 794 titles and abstracts, we identified 17 studies (13 full articles and 4 conference abstracts) relevant to the PICOST question (see Fig. 1 and Supplementary Material). The included studies consisted of one randomised trial (RCT),⁸ one prospective before-and-after studies,¹⁸ two observational cohort studies,19, 20 one case series involving three patients,²¹ and 12 simulation studies.9, 10, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31 Only three simulation studies assessed a pediatric scenario.24, 27, 31 Table 2, Table 3 present a summary of the main settings and findings.

Fig. 1.

PRISMA flowchart.

Table 2.

Summary of results for clinical studies.

Author, year	Design/ Country	Population/ Exposure	Participant Characteristics	Intervention/Control	Outcomes
Lee, 20238	Prospective randomized controlled study/South Korea	OHCA	BLS and ALS hospital providers	Flow sensor real-time visual ventilation feedback device (Zoll Accuvent)/No feedback	Intervention = 63, control = 58 ROSC (55.5 % vs. 36.2 %, p = 0.04) 30 h survival (49.2 % vs. 46.5, p = 0.001). Survival to discharge (4.9 % vs. 8.6 %, p = 0.54) Survival with good outcome (11.1 vs. 10.3, p = 0.77) No data on ventilation measures reported
Drennan, 202418	Prospective before-after study/Canada	OHCA	BLS and ALS EMS providers	Flow sensor real-time visual ventilation feedback device (Zoll Accuvent)/No feedback	Intervention = 221, Control = 191 ROSC (27 % vs. 29 %, p = NS) Ventilation rate (12 (IQR 10, 17) vs. 14 (11, 19), p = 0.035) Prop rate in target (53 %±38 vs. 29 %±9, p < 0.001) Insufflation volume measured (401 ml (353, 472) vs. 374 (274, 453), p = 0.058) Proportion volume in target (28 %±17 vs. 21 %±16, p < 0.001) Proportion volume & rate in target (19 %±17 vs. 7 %±10, p < 0.001)
Gerber, 202321	Case series/USA	OHCA	EMS providers ED hospital providers	Fow sensor real-time visual ventilation feedback device (Zoll Accuvent)/No control group Comparison between EMS providers vs. hospital staff after ED admission	Total number of subjects = 3 Case 1: Rate 8/min vs. 17/min Mean insufflation volume measured 500 ml vs. 844 ml Case 2: Rate 6/min vs. 15/min Mean insufflation volume measured 382 ml vs. 610 ml Case 3: Rate 10/min vs. 14/min Mean insufflation volume delivered 478 ml vs. 638 ml
Lemoine, 202419	Prospective cohort study, abstract only/France	OHCA	BLS EMS providers	Flow sensor real-time visual ventilation feedback device (EOlifeX®)/no control group	N = 104 Mean insufflation volume measured: 538 [IQR 412–645] ml Volume measured with passive exhalation: 291 [219–405] ml Leakage: volume 199 [119–287] ml, ratio 41 % [26–54 %] intervention-time showed a slight improvement in leakage in ventilation 2 compared to one in 30:2 ratio
McCarty, 201220	Prospective cohort study, abstract only/USA	ED	ED hospital providers	CO2/Flow sensor real-time visual ventilation feedback device (NICO monitor, Philips)/no control group	N = 11 Ventilation rates 17/min (IQR 11,20) Insufflation volume measured 707 ml (IQR 564,827)

ROSC: Return of Spontaneous Circulation, IQR: Interquartile Range, BV: Bag valve, OHCA: out-of-hospital cardiac arrest, IHCA: in-hospital cardiac arrest, EMS: Emergency medical services, ALS: Advanced Life Support, BLS: Basic life support, EMT: Emergency Medical Technician, ED: Emergency Department.

Table 3.

Summary of results for simulation studies.

Author, year	Design/ Country	Population/ Exposure	Participant Characteristics	Intervention/Control	Outcomes
Gould, 202023	Simulation study/USA	Mannikin Adult resuscitation scenarios	BLS and ALS EMS providers	Flow sensor real-time visual feedback device (Zoll AccuVent)/no feedback	N = 20 Ventilations in target for: Rate (71 % vs. 41 %, p < 0.001) Insufflation volume measured (79 % vs. 31 %, p < 0.001), Both (63 % vs. 10 %, p < 0.001).
Heo, 202024	Simulation study/Korea	Mannikin Adult and pediatric resuscitation scenarios	BLS (n = 4) and ALS (n = 22) hospital providers	Flow sensorreal-time visual feedbackdevice (Zoll AccuVent)/no feedback	N = 26 Adult BV: Insufflation volume measured: 432 ± 64 vs. 393 ± 136 Optimal insufflation volume measured: 47.3 % vs. 18.5 % Optimal ventilation interval: 95.6 % vs. 50.2 % Pediatric BV Insufflation volume measured: 145 ± 23 vs. 131 ± 34 Optimal insufflation volume measured: 89.51 % vs. 72.66 % Optimal ventilation interval: 95.83 % vs. 57.14 % all p value < 0.001
Khoury, 201910	Simulation study/France	Mannikin Adult resuscitation scenarios	BLS (n = 20) and ALS (n = 20) EMS providers	Flow sensor (EOlifeX®) visual ventilation feedback for manual ventilation/no feedback	N = 40 ALS Group (ETT): Ventilation rate: 10.7 ± 1.1 vs. 16.2 ± 6.9 Insufflation volume measured: 529 ± 43 vs. 549 ± 153 Inspiratory time: 1.3 ± 0.5 vs. 1.2 ± 1.5 I/E ratio: 0.3 ± 0.1 vs. 0.5 ± 0.2 Optimal ventilation volume (defined as insufflation volume between 300 and 600 ml and rate between 8 and 15/min): 85 % vs. 15 % BLS group (bag mask): Ventilation rate: 10.8 ± 1.1 vs. 18.2 ± 8.0 Insufflation volume measured: 451 ± 86 vs. 549 ± 153 Inspiratory time: 1.3 ± 0.5 vs. 1.2 ± 1.5 I/E ratio: 0.3 ± 0.3 vs. 0.6 ± 0.2 Optimal ventilation: 90 % vs. 15 % all p value < 0.001
Kim, 20209	Simulation study/Korea	Bench model	Senior hospital providers and EMT students	Flow sensor (Amflow®) real-time visual portable feedback device/no feedback	N = 40 Insufflation volume measured: 505.6 ± 32.2 vs. 534.2 ± 73.5, p = 0.012 Accurate volume range: 85.4 % vs. 41 %, p < 0.001 Ventilation rate: 10 (IQR 10,10) vs. 9.4 (8.2, 12.2), p = 0.62 Accurate rate: 99.2 % vs. 12.5 %, p < 0.001
Lyngby, 202125	Simulation study/Denmark	Mannikin Adult resuscitation scenarios	BLS (n = 27) and ALS (n = 5) EMS providers	Pressure flow sensor (Zoll AccuVent) real-time visual feedback/no feedback	N = 32 Ventilations in target for: Rate 97 % vs. 67 %, p < 0.001 Volume 77.5 % vs. 53 %, p < 0.001 Both 75 % vs. 22 %, p < 0.001
Charlton, 202122	Simulation study/UK	Mannikin Adult resuscitation scenarios	BLS (n = 28) and ALS (n = 78) EMS providers	Pressure flow sensor (Zoll AccuVent) real-time visual feedback system/no feedback	N = 106 Insufflation volume within recommendation: 94.3 % vs. 22.7 % Mean Insufflation volume: 546 (IQR 531–560) vs. 630 (518–725) Ventilation within recommendation: 94.3 % vs. 51 % Median Ventilation rate: 9 (IQR 9–9) vs. 10 (8–14) (McNemars test p = <0.0001).
Scott, 202126	Simulation study/USA	Mannikin Adult resuscitation scenarios	ALS hospital providers	CO2/Flow sensor real-time visual ventilation feedback device (NICO, Philips)/no feedback	N = 52 Ventilatory rate: 10.7 (IQR 7.9–13.8) vs. 9.8 (8.0–13.5), p = 0.79 Before feedback Insufflation volume measured appeared to be impacted among participant by sex, glove size.
Wagner, 202227	Simulation study/Austria	Mannikin Pediatric resuscitation scenarios	ALS hospital providers	Pressure flow sensor (Neo Training) real-time visual feedback system/no feedback	N = 40 Volume (ml/kg): Inspiratory 10.15 ± 4.6 vs. 12.83 ± 6.0, p = 0.002 Expiratory 6.81 ± 2.6 vs. 7.34 ± 3.5, p = 0.174 Mask leak (%) 24.10 ± 18.6 vs. 31.76 ± 23.4, p = 0.009 Dwell time on feedback devices was high, reducing attention to the infant's chest and mask.
You, 201728	Simulation study/South Korea	Mannikin Adult resuscitation scenarios	BLS (n = 10) and ALS (n = 42) EMS and hospital providers	Flow sensor tidal volume monitoring device/no feedback	N = 14 Optimal ventilation (%): 84.3 ± 12.1 vs. 31.8 ± 22.8, p < 0.001 Ventilation interval (s): 6.1 ± 0.1 vs. 6.1 ± 0.1, p = 0.29
Tran Dinh, 202330	Simulation study, abstract only/France	Manikin Adult resuscitation scenarios	Medical students trained at ALS level of care	Flow sensor (EOlifeX®) visual ventilation feedback/no feedback	N = 344 Ventilation volumes (ml): 468 ± 90 vs. 625 ± 162, p < 0.0001) Insufflation times (ms): 1478 ± 580 vs. 1180 ± 417, p < 0.0001
D'Agostino, 202429	Simulation study, letter to editor/Italy	Mannikin Adult resuscitation scenarios	ALS hospital providers	Flow sensor (EOlifeX®) visual ventilation feedback/instructor evaluation of ventilation quality	Correct ventilation assessment Rate: 45 % with feedback vs. 100 % instructor, p < 0.001 Volume: 5 % with feedback vs. 100 % instructor, p < 0.001
Lemoine, 202431	Simulation study, abstract only/France	Mannikin Adult and pediatric resuscitation scenarios	BLS EMS provider	Blinded Flow sensor (EOlifeX®) visual ventilation feedback/no control group	Pediatric simulation (3 years – 14 kg manikin) Insufflation volume: 139 ml [IQR 89–193] Volume exhaled: 117 ml [IQR 78–163] insufflation time: 758 [IQR 560–1019] ms Exsufflation time: 326 [254–385] ms Leakage ratio: 11 % [4–19] Prop in target volume: 13 % [6–8 ml/kg]

ROSC: Return of Spontaneous Circulation, IQR: Interquartile Range, BV: Bag valve, OHCA: out-of-hospital cardiac arrest, IHCA: in-hospital cardiac arrest, EMS: Emergency medical services, ALS: Advanced Life Support, BLS: Basic life support, EMT: Emergency Medical Technician, ED: Emergency Department.

Patient outcomes

For clinical outcomes of survival to discharge, survival with good neurological outcome at discharge and ROSC we identified one single-centre RCT⁸ and one prospective before-after studies reporting clinical outcomes.¹⁸

In the RCT,⁸ adult patients (n = 121) were randomised to either real-time visual ventilation feedback using a pressure-flow sensor compared with no audio-visual ventilation feedback. No differences between groups were reported for rates of survival to discharge or rates of survival and survival with good neurological outcome at 80 days. A significant increase was seen for ROSC (55.5 % vs. 36.2 %, p = 0.04) and 30-h survival (49.2 % vs. 46.5 %, p = 0.001) with audio-visual ventilation feedback. The study reported no data on ventilation quality, and the data were not adjusted for differences reported between the groups (e.g. more cardiac arrests occurred in public in the feedback group).

A prospective before-after clinical study¹⁸ included 412 adult patients (221 in the ventilation feedback group) and examined the introduction of a visual real-time ventilation feedback device using a pressure-flow sensor. This study showed no difference in unadjusted ROSC (27 % vs. 29 %, p = NS) between groups. An adjusted exploratory analysis showed neither ventilation rate (OR 1.11, 95 %CI 0.99 to 1.26, p = 0.08) or insufflation volume delivered into the bag valve mask (BVM), supraglottic airway (SGA) or endotracheal tube (ETT) OR 1.07, 95 %CI: 0.93 to 1.25, p = 0.35) were associated with ROSC.

Ventilation parameters

Ventilation rate and insufflation volume

Drennan et al.¹⁸ observed an improvement in rate and insufflation volume assessed with the use of real-time ventilation feedback designed to measure insufflation volume. Ventilation rate decreased from 14 (IQR 11, 19) to 12 (IQR 10, 17) (p = 0.035). When examined by the proportion within the targeted range, improvements were seen for ventilation rate (53 % ± 38 vs. 29 % ± 9, p < 0.001), insufflation volume (28 % ± 17 vs. 21 % ± 16, p < 0.001) and insufflation volume and rate combined (19 % ± 17 vs. 7 % ± 10, p < 0.001).

The three other observational clinical studies or case series did not compare ventilation parameters with or without real time feedback but used the devices to blindly assess insufflation volume measured, rate delivered during CPR²¹ and volume measured with passive exhalation.¹⁹ When blinded to the feedback device, rate and insufflation volume measured exceeded guideline recommended ventilation parameters,19, 20 moreover in one study volume measured with passive exhalation and calculated leakage were improved with feedback device.¹⁹ One study, comparing ventilation delivered by EMS providers to hospital staff immediately after ED admission observed significant variation in insufflation volume measured and rate delivered (volume and rate delivered by hospital staff exceeded EMS providers in all 3 cases reported).²¹

Twelve simulation studies assessed a visual feedback device using a flow, and/or pressure-based flow sensor technology assessed insufflation volume and ventilation rate during CPR.9, 10, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31

In ten simulation studies, visual real-time feedback was compared to no feedback.9, 10, 22, 23, 24, 25, 26, 27, 28, 30 A significant improvement in insufflation volume was reported in all studies with feedback. Ventilation rates were also significantly improved, as did compliance with current guidelines in four of eight studies.9, 10, 22, 23, 24, 25, 26, 27, 28

One simulation study observed, when providers were blinded to the feedback device, a significant variation in insufflation volume measured according to sex of provider (587 ± 168 ml for female vs. 685 ± 134 ml for male, p = 0.05) or size of gloves (618 ± 114 ml for small, 566 ± 181 ml for medium and 728 ± 153 ml for large, p = 0.027).²⁶

One simulation study compared visual feedback device use with the rate and insufflated volume visually assessed and estimated by trained instructors. Instructors seemed to overestimate significantly the compliance with guidelines for rate and volume delivered by students.²⁹

Only three studies assessed pediatric bag valve ventilation in manikins.24, 27, 31 Heo et al observed a significant improvement in the proportion of adequate insufflation volume measured (IV) and ventilation intervals (VI) with real-time feedback (IV:89.51 % vs. 72.66 %, VI: 95.83 % vs. 57.14 %, all p value < 0.001).²⁴ Lemoine et al assessed in a simulated 3-year old manikin setting, the performance of BLS providers to perform adequate ventilation. They observed a low proportion (13 %) of ventilation in target insufflation volume measured.³¹ Wagner et al observed a decrease in insufflation volume measured (10.15 ± 4.6 mL/kg vs. 12.83 ± 6.0 mL/kg, p = 0.002) and a decrease in mask leak (24.10 %±18.6 vs. 31.76 %±23.4, p = 0.009) using ventilation feedback. They also observed that participants’ subjective workload rating increased by 3.5 % (P = 0.018) and 8 % (P < 0.001) when provided with feedback.²⁷

Discussion

Real-time ventilation feedback devices are now available to monitor and improve real-time ventilation for basic life support providers. They offer the opportunity to measure both ventilation rate and insufflation volume during cardiopulmonary resuscitation (CPR) with the potential to improve patient outcomes. However, in this review, we found scant evidence on the effect of these devices on clinical outcomes and inconsistent data on ventilation parameters. Both clinical and simulation studies showed inconsistent results in ventilation metrics measured, such as ventilation rate and volume insufflated through the mask or the ETT or guideline compliance.

Intra-arrest ventilation during CPR with or without an advance airway is challenging. In an observational study assessing bag valve mask ventilation using bioimpedance during CPR on 1976 patients, Idriss et al. observed that 60 % of patients had measured lung inflation in less than 50 % of the ventilation pauses during CPR with a 30:2 compression-to-ventilation ratio. Patients with more than 50 % ventilation measured by bioimpedance during CPR had higher odds of ROSC, survival and favorable neurologic outcome.⁷ While improving ventilation during CPR has biological plausibility to improve outcome by enhancing oxygen delivery to the heart and brain and mitigating acidemia, the current evidence is weak and tools to measure ventilation during CPR have historically been limited.³²

Ventilation and chest compression are interconnected, and the measure of volume (both insufflated, residual versus tidal and exsufflated) as well as passive ventilation during CPR needs to be clearly defined and measured. A recent paper tried to define concepts and terminology related to intra-arrest ventilation.³³ Most of the identified studies incorrectly labeled the amount of airflow measured at the mask or the advanced airway as tidal volume. We suggest avoiding using the term tidal volume for this measurement, since tidal volume represents the amount of air that moves in or out of the lungs with each respiratory cycle. This parameter is not directly measured in any of the published studies, with the devices used in most included studies measuring the insufflation volume as it passes into the mask or the advanced airway. In one clinical study¹⁹ and two simulation studies27, 31 the volume exhaled was measured in addition as it passed between the airway or mask through the device. We acknowledge that the current development of real-time ventilation feedback devices offers a unique opportunity to measure the ventilation rate and the insufflation volume measured before the mask or the advanced airway during CPR. Whether doing so indirectly measures the quality of ventilation and contributes significantly to affect oxygen delivery during CPR or improves outcomes remains unknown.

Interestingly, several studies observed differences in ventilation delivered during CPR during training; this difference might be related to the training, sex, and size of the rescuers.26, 29 These devices could provide a means to achieve objective measurement, standardize training, and limit individual variations during CPR. ILCOR currently recommends the use of CPR feedback devices during resuscitation training for healthcare providers and lay providers.¹⁶ Similar to high-fidelity manikins, ventilation feedback devices using pressure-flow sensors seem to offer a way to help learners to achieve the ventilation goals without the subjectivity of the trainers.²⁹

Pediatric studies were especially limited, with only three included.24, 27, 31 One additional study by Chapman et al.,³⁴ which was not included due to not meeting inclusion criteria, found that a quality improvement initiative incorporating audiovisual feedback tools, such as a CPR metronome, ventilation reminder cards, and structured team debriefings, significantly reduced the proportion of CPR time with clinically significant hyperventilation (≥30 breaths per minute) from 51 % to 29 %, and decreased median ventilation rates from 30 bpm to 21 bpm. These findings highlight the critical need for more pediatric-focused studies evaluating the impact of real time audiovisual feedback on ventilation quality during CPR. Given the rarity of pediatric cardiac arrest events, we hypothesize that a bundled intervention combining realtime ventilation feedback, education, cognitive aids, and team-based feedback may be more effective than single-modality approaches in improving resuscitation quality.

Device registration with regulatory authorities alone does not provide evidence of device performance in real-world settings. As rescuer and patient factors influence high-quality ventilation delivery, further research is required to demonstrate the role and clinical efficacy of real-time ventilation feedback devices.

Knowledge gaps

This scoping review has highlighted several knowledge gaps. The ideal targets or goals for ventilation during CPR have not been defined, and current guidelines are based on low-quality evidence. The performance of the different devices has not been assessed in clinical data compared to validated measurements. In particular, measuring true tidal and exhaled volumes (to assess leak) during CPR needs to be validated.³³ There is a current lack of evidence of clinical efficacy (i.e. whether the devices work in optimal settings) or clinical effectiveness (real-world settings) for adults and pediatrics. Seven of 19 studies were either sponsored or performed directly by industry. Investigator driven research independent of industry should be encouraged on the topic.

Limitations

This scoping review has several limitations that should be considered when interpreting the findings. First, although we conducted a comprehensive search across multiple databases and included grey literature, it is possible that relevant studies were missed, particularly unpublished data or studies not indexed in the selected databases. Second, the inclusion of conference abstracts and simulation studies, while necessary to capture the breadth of available evidence, limits the strength of conclusions due to their often-preliminary nature and lack of peer-reviewed methodological detail. Third, the heterogeneity in study designs, populations, interventions, and outcome measures precluded quantitative synthesis and limited direct comparisons across studies. Fourth, while we included studies without control groups to map the full scope of available evidence, this may have introduced bias and reduced the ability to assess causality. Finally, the majority of included studies were conducted in simulated settings, and only a few reported clinical outcomes, limiting the generalizability of findings to real-world practice. These limitations underscore the need for high-quality, prospective clinical studies to evaluate the effectiveness of real-time ventilation feedback devices in improving patient outcomes during cardiac arrest.

Conclusion

We found scant evidence of the effect of real-time ventilation feedback devices on clinical outcomes and the ventilation parameters. Clinical evaluation of the clinical effectiveness of real-time ventilation feedback devices is needed.

CRediT authorship contribution statement

Guillaume Debaty: Writing – original draft, Visualization, Validation, Methodology, Investigation, Data curation, Conceptualization. Nicholas J. Johnson: Writing – review & editing, Methodology, Investigation, Data curation, Conceptualization. Maya Dewan: Writing – review & editing, Investigation, Data curation, Conceptualization. Laurie J. Morrison: Writing – review & editing, Validation, Supervision, Methodology, Data curation, Conceptualization. Janet E. Bray: Writing – review & editing, Visualization, Validation, Supervision, Methodology, Investigation, Data curation, Conceptualization. Michael Smyth: . Theresa Olasveengen: . Rebecca Cash: . Julie Considine: . Sung Phil Chung: . Vihara Dassanayake: . Katie Dainty: . Bridget Dicker: . Fredrik Folke: . Anthony Lagina: . George Lucas: . Carolina Malta Hansen: . Takanari Ikeyama: . Siobhan Masterson: . Ziad Nehme: . Tatsuya Norii: . Gavin Perkins: . Violetta Raffay: . Giuseppe Ristagno: . Aloka Samantaray: . Baljit Singh: . Christopher M. Smith: . Christian Vaillancourt: . Federico Semeraro: . Peter Morley: .

Funding

This Scoping review was funded by the American Heart Association, on behalf of The International Liaison Committee on Resuscitation (ILCOR). None of the authors received payment from this funding source to complete this scoping review. JB receives a Fellowship from the National Heart Foundation of Australia (#104751).

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Appendix B. Supplementary material

The following are the Supplementary data to this article: