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

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.

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.