Rhythm Analysis during Compressions: A systematic review update (BLS_2211)

Conflict of Interest Declaration

The ILCOR Continuous Evidence Evaluation process is guided by a rigorous ILCOR Conflict of Interest policy. The following Task Force members and other authors were recused from the discussion as they declared a conflict of interest: none applicable

The following Task Force members and other authors declared an intellectual conflict of interest and this was acknowledged and managed by the Task Force Chairs and Conflict of Interest committees: none applicable

CoSTR Citation

Lukas G, Bray J, Perkins G, Morley P, Olasveengen TM, For the International Liaison Committee on Resuscitation (ILCOR) Basic Life Support Task Force. Rhythm check during Compressions: A systematic review update

Available from: http://ilcor.org

Methodological Preamble and Link to Published Systematic Review

Rhythm checks during CPR are essential for assessing cardiac rhythm and determining the need for defibrillation. However, these pauses disrupt chest compressions, which are critical for maintaining coronary and cerebral perfusion. Optimizing rhythm checks to minimize interruptions is crucial for improving outcomes. Technologies like “see-through CPR” allow real-time rhythm assessment without stopping compressions by filtering artifact from chest compressions. While validation studies suggest high sensitivity and potential improvements with AI, (Brown 2022) the previous ILCOR reviews found no clinical outcome studies (https://costr.ilcor.org/document/analysis-of-rhythm-during-chest-compression-tfsr-costr). Since then, new studies have reported patient outcomes, prompting an updated review to incorporate recent evidence (Derkenne 2024, de Graaf 2021). Findings from the Adult literature were reviewed by the BLS Task Force and informed the Treatment Recommendations.

Systematic Review

Lukas G, Bray J, Perkins G, Morley P, Olasveengen TM, For the International Liaison Committee on Resuscitation (ILCOR) Basic Life Support Task Force. Rhythm check during Compressions: A systematic review update (in preparation)

PICOST

The PICOST (Population, Intervention, Comparator, Outcome, Study Designs and Timeframe)

Population: Adults in any setting (out-of-hospital or in-hospital cardiac arrest)

Intervention: Analysis of cardiac rhythm during chest compressions

Comparators: Analysis of cardiac rhythm during pauses in chest compressions

Outcomes: Survival to hospital discharge with good neurological outcome and survival to hospital discharge/30-days were ranked as critical outcomes.

Return of spontaneous circulation (ROSC) and CPR quality metrics (e.g. chest compression fraction, pauses in compressions, and compressions per minute) were included as important outcomes.

Study Designs: Randomized controlled trials (RCTs) and non-randomized studies (non-randomized controlled trials, interrupted time series, controlled before-and-after studies, cohort studies) are eligible for inclusion. Studies reporting the development or validation of artifact-filtering algorithms were excluded. Unpublished studies (e.g., conference abstracts, trial protocols) are excluded. All relevant publications in any language are included as long as there is an English abstract

Timeframe: September 23^rd 2019 to March 17 2025

PROSPERO Registration CRD42024627999

Consensus on Science

This systematic review update identified 533 studies, with 57 duplicates removed. After title and abstract screening (368 studies), 12 underwent full-text review, of which 10 were excluded (5 conference abstracts, 5 incorrect outcomes). Ultimately, 2 observational studies (Derkenne 2024, de Graaf 2021) met eligibility criteria, both focusing on software-based cardiac rhythm analysis during CPR in OHCA patients.

Survival to hospital discharge with good neurological outcome and survival to hospital discharge

For the critical outcomes of survival to hospital discharge with good neurological outcome and survival to hospital discharge/30 days, we identified very low certainty evidence (downgraded for serious risk of bias and inconsistency) from one observational study (Derkenne 2024).

In this study, 570 OHCA patients were treated with either the Analyse While Compressing (AWC) algorithm (n=285, 2021-22) or a conventional defibrillation algorithm (n=285, 2017). Both groups received BLS care from firefighter teams using ERC 2015 guidelines and the DEFIGARD Touch 7 AED. The AWC algorithm allowed real-time rhythm analysis during chest compressions, triggering an earlier rhythm check if VF was detected. In the control group, rhythm checks occurred at fixed two-minute intervals. There was no significant difference in survival to hospital discharge between groups (adjusted hazard ratio: 0.96 [95% CI, 0.78–1.18], p=0.49). However, in a subgroup of OHCA in public locations with call-to-AED time <12.5 min, survival was higher with AWC (adjusted hazard ratio: 0.83 [95% CI, 0.73–0.93]).

Return of Spontaneous Circulation

For the important outcome of ROSC we identified no studies.

CPR Quality Metrics

For the important outcome of CPR quality metrics, we identified very low certainty evidence (downgraded for serious risk of bias) from two observational studies (De Graaf 2021; Derkenne 2024).

In the observational study by De Graaf (2021), 783 OHCA patients were treated with AEDs using either the cprINSIGHT algorithm (Stryker LIFEPAK CR2, 2018–2019) or conventional AEDs (Stryker LIFEPAK 1000, 2016–2017). The cprINSIGHT algorithm allowed real-time rhythm analysis during chest compressions by using transthoracic impedance filtering to classify rhythms as shockable, non-shockable, or inconclusive. If shockable, the AED pre-charged and delivered the shock at the end of the two-minute cycle, whereas a non-shockable rhythm resulted in uninterrupted CPR. The intervention group had a higher chest compression fraction (CCF) (86% [IQR 79–92] vs. 80% [IQR 73–86], p < 0.001) and shorter pre-shock pause (8s [IQR 7–11] vs. 22s [IQR 20–24], p < 0.001) and peri-shock pause (12s [IQR 10–16] vs. 25s [IQR 22–29], p < 0.001).

In the observational study by Derkenne (2024), 570 OHCA patients were treated using either the Analyse While Compressing (AWC) algorithm (n=285, 2021–2022) or a conventional defibrillation algorithm (n=285, 2017). The primary outcome of CCF was significantly higher in the intervention group (77% [72–80] vs. 72% [67–76], p < 0.001). Several secondary CPR metrics were improved in the intervention group, including increased prompt CCF during CPR phases, reduced hands-off times (pre-shock, peri-shock, and post-shock), shorter analysis and CPR phase durations, and improved shock delivery timing in cases of ventricular fibrillation storm. There was no significant difference in chest compression rate between groups. Differences were noted in the time spent in shockable, organized, and asystolic rhythms.

Good Practice Statement

We suggest the usefulness of artifact-filtering algorithms for analysis of electrocardiographic rhythm during CPR be assessed in clinical trials or research initiatives (weak recommendation, very low certainty of evidence)

Justification and Evidence to Decision Framework Highlights

The BLS Task Force prioritized this topic due to new observational studies published since the 2019 systematic review, which previously found no human studies addressing survival outcomes or CPR quality metrics such as chest compression fraction (CCF), pauses in compressions, compressions per minute, and time to first shock.

This updated review identified two observational studies (De Graaf 2021, Derkenne 2024), both downgraded from low to very low certainty due to methodological limitations. These studies evaluated software-based rhythm analysis during CPR. Both studies showed improved CPR quality metrics with rhythm analysis during compressions, but neither assessed survival or neurological outcomes.

The table below compares their sensitivity and specificity against American Heart Association (AHA) performance goals:

Both studies were observational with historical controls, meaning unknown factors may have influenced results. The non-blinded design further limits confidence in the findings. Neither study assessed survival or neurological prognosis, making it unclear whether these technologies improve patient outcomes.

The BLS Task Force concluded that the evidence is insufficient to make a Treatment Recommendation, given the absence of RCTs or well-controlled observational studies. Additionally, the potential costs of implementing new technology without proven clinical benefit were considered. No evidence of harm was found, but the current data do not justify routine use. Instead, the Treatment Recommendation has been replaced with a Good Practice Statement, suggesting that artifact-filtering algorithms for rhythm analysis during CPR should be further evaluated in clinical trials or research initiatives. The task force encourages EMS systems already using these technologies to report their experiences to help build a stronger evidence base.

Knowledge Gaps

1. Absence of Randomized controlled trials looking at critical or important outcomes

2. Absence of Observational studies with adequate comparisons looking at critical or important outcomes

ETD summary table: BLS 2211 Rhythm analysis during compressions ETD

References

1. Babini et al. Optimizing defibrillation during cardiac arrest. Curr Opin Crit Care 2021; 27:246–254 DOI:10.1097/MCC.0000000000000821
2. Bray et al. Wolf Creek XVII Part 6: Physiology-Guided CPR. Resus Plus 2024;18:100589. https://doi.org/10.1016/j.resp...
3. Brown et al. Role of artificial intelligence in defibrillators: a narrative review. Open Heart 2022; 9:e001976. doi:10.1136/ openhrt-2022-001976
4. Derkenne et al. Analysis during chest compressions in out-of-hospital cardiac arrest patients, a cross/sectional study: The DEFI 2022 study. Resuscitation 2024;202:110292
5. De Graaf et al. Analyzing the heart rhythm during chest compressions: Performance and clinical value of a new AED algorithm. Resuscitation 2021; 162:320-328
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