Systematic Reviews
Copyright ©The Author(s) 2025.
World J Crit Care Med. Sep 9, 2025; 14(3): 103402
Published online Sep 9, 2025. doi: 10.5492/wjccm.v14.i3.103402
Table 1 Summary of included studies, n (%)
Ref.
Ecker et al[20], 2020
Perry et al[19], 2020
Johnsen et al[24], 2008
Lee et al[11], 2011
Peltan et al[15], 2022
Lee et al[9], 2021
Sonkin et al[21], 2022
Meinich-Bache et al[25], 2018
Kim et al[8], 2021
ComparatorsVideoAudioControlVideoAudioFilmingVideoVideoAudioTelemedicineControlVideoAudioVideoVideoSmartphoneBLS
CountryGermanyIsraelNorwaySouth KoreaUnited StatesSouth KoreaIsraelNorwaySouth Korea
Study period2018-20202018-20192006-2007May 2010 to June 20102017-20182018-20192020-20212017-20182015-2016
Study designRandomised controlled simulation trialA simulation studyA simulation studyRandomised controlled simulation trialMulticenter randomized controlled trialRetrospective cohort studyA Simulation studyA Simulation studyRetrospective cohort study
Sample size50505014171863939353638717224319199417
ParticipantsAdult volunteersMedical techniciansDispatchersAdult volunteersPhysicianadult patients with OHCAActive paramedicsBystander and dispatcherAdult patients with OHCA
Inclusion criteriaAdult volunteers were recruited from the streets surrounding the hospital. Exclusion criteria included age less than 18 and more than 65 years, healthcare providers (medical practitioners, nurses, paramedics), pregnancy, cardiovascular or musculoskeletal diseases, or any other medical condition preventing performance of CPR over 8 minutesTwenty-five emergency medical technicians acted as EMDs in the three conditions. A mannequin measured five factors that determined the effectiveness of the chest compressionsAll had previously assisted CPR in their ordinary work. None of them had used video for dispatcher instructions prior to the trialsThe volunteers were lay people without any previous CPR training. The subjects who had difficulty performing compression-only CPR due to their physical condition, those who were not familiar with cellularphone usage and those who had difficulty watching a video on a cellular phone due to poor vision were excluded from the studyAll personnel involved in ward-based IHCA resuscitation at each study site were eligible to participate in the study. Composition and training of these ad hoc resuscitation teams varied by study siteAfter excluding unknown, nonbystander-witnessed arrest cases, and EMS-witnessed arrests cases (n = 2648), presumed non-cardiac etiology (n = 256), and pediatric cases (n = 28), 2109 cases were eligible for the final analysisActive paramedics at MDA ambulance teams at the time of the studyNo specefic criteriaWe include adult patients (n = 18) with OHCA of medicalcauses and EMS-attended and dispatchedin. SALS isanadvanced field resuscitation including drug administration by paramedics with video communication-based direct medical direction
Age (years)32.92 (12.5)37.6 (13.9)36.7 (13.9)NRNRNR33.556.6 ± 7.255.3 ± 6.2NRNR64.9 ± 16.272.2 ± 14.7NRNRNR82 (77-87)80 (72-86)
BMI (kg/m2)24.2 (5.7)23.7 (3.6)23.4 (3.7)NRNRNRNRNRNRNRNRNRNRNRNRNRNRNR
Male19 (38)15 (30)13 (26)NRNRNR120 (51.3)19 (48.7)NRNR263 (68)1087 (63.1)30 (70)NRNR79 (39.7)207 (49.6)
Female31 (62)35 (70)37 (74)NRNRNR519 (48.7)20 (51.3)NRNR124 (32.0)635 (36.9)13(30)NRNR120 (60.3)210 (50.4)
Has provided CPR1 (2)1 (2)1 (2)NRNRNRNR3939NRNRNRNR32NRNRNRNR
Witnessed an emergency5 (10)8 (16)6 (12)NRNRNRNR3939NRNRNRNR32NRNRNRNR
Had first aid course47 (94)47 (94)50 (100)NRNRNRNRNRNRNRNRNRNR32NRNRNRNR
BLS: Basic life support; BMI: Body mass index; CPR: Cardiopulmonary resuscitation; EMD: Emergency medical dispatcher; NR: Not reported; IHCA: In-hospital cardiac arrest; OHCA: Out-of-hospital cardiac arrest; EMS: Emergency medical services; MDA: Magen david adom; SALS: Smartphone-based advanced cardiac life support.
Table 2 Inclusion of a summary of the studies, n (%)
Ref.
Linderoth et al[22], 2021
Ofoma et al[26], 2022
Plata et al[18], 2021
Lee et al[27], 2021
Aranda-García et al[16], 2023
Pérez Alonso et al[14], 2017
Lee et al[28], 2020
Ecker et al 2021[35]
Yang et al[29], 2009
ComparatorsVideoTelemedicineNo telemedicineVideoV-DACPR with rapid transitionV-DACPR with delayed transitionC-DACPRVideoAudioGGControlVideoAudioAudio and video telephonyVideoAudio
CountryDenmarkUnited StatesGermanySouth KoreaSpainSpainSeoul, South KoreaGermanyTaiwan
Study period2019-2021July 1, 2017, and December 31, 2019September 2019 to February 2020October 2019 to July 20202021-2022November 2014 to July 20152017August to September 20182009
Study designRetrospective studyA prospective, voluntary, multi-site registry of IHCARandomised controlled simulation trialRandomised controlled simulation trialRandomised controlled simulation trialRandomised clinical simulationRetrospective cohortProspective randomized pilotRandomized controlled study
Sample size9014373302129343454314143636231148954 venues with realistic full-scale CPR mannequin4353
ParticipantsBystanderAdult patientsParamedics and emergency physiciansBystanderAdult volunteersNurseEmergency medical techniciansBystanderVolunteers (bystander)
Inclusion criteriaThe training included simulation-based scenarios with unconscious patients and cardiac arrest cases with a focus on high-quality CPR with simultaneously real-time guidance (video-instructed DA-CPR)We identified 70881 patients 18 years or older with an index pulseless IHCA between July 1, 2017, and December 31, 2019. We excluded arrests at hospitals that did not respond to the AHA surveys or had missing information on TCC availability; at hospitals with less than 10 cardiac arrests over the study period; that occurred outside of an ICU or hospital ward (e.g., emergency room and operating room); and in patients with an implantable cardioverterdefibrillator. Additionally, we excluded patients with missing information related to arrest time or survivalNo specefic criteriaVolunteers aged 18 years or older were recruited for the simulation trial from October 2019 to July 2020. Healthcare providers, and participants with chronic lung diseases, cardiovascular diseases, visual disabilities, or hearing disabilities were excluded during initial enrollment. Written consent was obtained from all participantsInclusion criteria were no theoretical or practical training on BLS in the previous 2 yearsTraining in BLS in the last 2 years and a minimum of 2 years of professional experience in emergency services as well as familiarity with the use of AED and the ALSOHCA patients with a presumed cardiacetiology who were more than 18 years of age between January and December 2017NRNinety-six adults without CPR training within 5 years were recruited
Age (years)21.25 (11.17)65.5 (15.4)65.6 (15.1)NR30.5 (12.0)29.1 (10.2)30.8 (12.1)232333 ± 832 ± 7NRNRNRNR50.1 ± 11.550.4 ± 12.7
BMI (kg/m2)NRNRNRNRNRNRNR22.522.1NRNRNRNRNRNRNRNR
Male508500 (59.1)17724 (58.7)NR10119141439%28%NRNRNRNRNRNR
Female405873 (40.9)12488 (41.3)NR3334340061%72%NRNRNRNRNRNR
Has provided CPR52NRNR93NRNRNRNRNRNRNRNRNRNRNR4 (70)1 (90)
Witnessed an emergency29NRNR93NRNRNRNRNRNRNRNRNRNRNR--
Had first aid course48NRNR93NRNRNRNRNRNRNRNRNRNRNR18 (60)18 (90)
BMI: Body mass index; CPR: Cardiopulmonary resuscitation; DA-CPR: Dispatcher-assisted cardiopulmonary resuscitation; NR: Not reported; IHCA: In-hospital cardiac arrest; OHCA: Out-of-hospital cardiac arrest; AHA: American Heart Association; TCC: Telemedicine critical care; ICU: Intensive care unit; V-DACPR: Video dispatcher-assisted cardiopulmonary resuscitation; T-DACPR: Telephone dispatcher-assisted cardiopulmonary resuscitation; BLS: Basic life support; AED: Automated external defibrillator; ALS: Advanced life support.
Table 3 Summaries of included studies, n (%)
Ref.
Morand et al[30], 2023
You et al[31], 2008
Barcala et al[17], 2023
Bolle et al[7], 2011
Bang et al[32], 2020
Bolle et al[33], 2009
Kim et al[8], 2021
Yuksen et al[23], 2016
Lee et al[34], 2018
ComparatorsVideoVideo telephony-directedVideo callsVideoAudioVideoAudioNon-guideVideoAudioVideoVoicePhysiciansEMTVideo
CountrySwitzerlandSouth KoreaSpainNorwaySouth KoreaNorwaySouth KoreaThailandSouth Korea
Study period2021200820212011Jun-19December 2006 and January 200720202014July to November 2015
Study designNRA prospective observational studyDescriptive and comparative designRandomized controlled trialProspective randomized simulationClinical trialMixed method designRetrospective studyRandomized trial
Sample size2852 public officers16909030303018012121414284848
ParticipantsBystanderPublic officersCoastal fshermenHigh school studentsLaypersonsHigh school studentsNRPhysicians, nurses and EMTParamedics
Inclusion criteriaNRNo previous experience with the use of a defibrillator participated in the studyProfessional fishermen with at least 10 years of experience (to ensure fully familiar with the boat and with performing tasks while sailing) who had not undergone BLS training in the previous 6 monthsHigh school students from Tromso were recruited as lay bystanders during regular school hoursAdult college students (age ≥ 18 years) and selected 90 participants who did not have formal training, such as the AHA BLS course, in CPR and AEDThe study population was selected during regular school hours without prior warningNRNRNR
Age (years)NRNR32.7 ± 6.846 ± 417.317.922.5 (22.0-26.25)22.0 (22.0-23.0)26 (23.0-25.0)17.317.922.33 ± 1.6722.42 ± 1.9827.64 ± 2.5630.64 ± 4.2929.68 ± 7.01333 (27-42)32 (25-43)
BMI (kg/m2)NRNR-------23.4 ± 5.123.9 ± 4.8
MaleNRNR69 (20)100%27%34%43 (30)36 (70)40%27%34%58 (30)33 (30)50%42 (90)82%70 (80)67 (40)
FemaleNRNR30 (80)0%73%66%56 (70)63 (30)60%73%66%41 (70)66 (70)50%57 (10)18%29 (20)32 (60)
Has provided CPRNRNR---83 (30)70%76 (70)--28 (60)7 (10)14 (30)-
Witnessed an emergencyNRNR--------
Had first aid courseNRNR--73%71%-----
BMI: Body mass index; CPR: Cardiopulmonary resuscitation; AHA: American Heart Association; BLS: Basic life support; CPR: Cardiopulmonary resuscitation; AED: Automated external defibrillator; NR: Not reported; EMT: Emergency medical technician.
Table 4 Individual study characteristics
Ref.
Design
Intervention
Results
Conclusion
Ecker et al[20], 2020Randomized controlled simulation trialThe participants received a smartphone to call emergency services, with emergency eye video-call in V-CPR group and normal telephone functionality in the other. Groups: T-CPR and V-CPR groups received standardized CPR assistance via phoneMean compression frequency of V-CPR group was 106.4, 11.7 minutes, T-CPR group 98.9, 12.3 minutes (NS), Unassisted group 71.6, 32.3 minutes (P < 0.001). Mean compression depth was 55.4, 12.3 mm in V-CPR, 52.1, 13.3 mm in T-CPR (P < 0.001) and 52.9, 15.5 mm. In unassisted (P < 0.001). Total percentage of correct chest. Compressions were significantly higher (P < 0.001) in V-CPR (82.6%), than T-CPR (75.4%) and unassisted (77.3%) groupsCPR was shown to be superior to unassisted CPR and was comparable to T-CPR. However, V-CPR leads to a significantly better hand position than other methods. With the other study groups. V-CPR assistance resulted in Volunteers performing chest compressions with more accurate compression depth. Despite reaching statistical significance, this may be of little clinical relevance
Perry et al[19], 2020A simulation studyA simulation study was conducted comparing CPR effectiveness under three conditions: Telephone-instructed, video-instructed, and video-instructed with the filming protocolCompared with telephone-instructed CPR, the filming protocol improved the proportion of time in which the bystander’s hands were in the correct position during chest compressions. Compared with video-instructed CPR, the filming protocol improved the proportion of time in which the chest was fully released after each compression and the proportion. Of time in which the compressions were conducted with an appropriate rhythm. The depth and rate of compressions did not. Improve the filming protocol conditionVideo-instructed CPR with the filming protocol improves CPR effectiveness compared to telephone- and Video-instructed CPR. Detailed implementation can improve new technology introduction
Johnsen et al[24], 2008 A simulation studyThey used video calls and traditional phone calls for the restVideo calls influenced the information base and understanding of the dispatchers. The dispatchers experienced that (1) Video calls help obtain information and provide, adequate functionality to support CPR assistance; (2) Their CPR assistance becomes easier; (3) The CPR might be of better quality; but (4) There is a risk of ‘‘noise’’Video communication can improve the dispatchers’ understanding of the rescuers situation, and the assistance they provide
Lee et al[11], 2011Randomized controlled simulation trialAdult volunteers were randomized to receive audio-assisted instructions (audio group = 39), or video-demonstrated instructions (video group = 39)For the video group, the chest compression rate was more optimal (99.5 minutes vs 77.4 minutes, P < 0.01), and the time from the initial phone call to the first compressions was shorter (184 seconds vs 211 seconds, P < 0.01). The depth of compressions was deeper in the audio group (31.3 mm vs 27.5 mm, P = 0.21), but neither group performed the recommended compression depth. The hand positions for compression were more appropriate in the video group (71.8% vs 43.6%, P = 0.01). As many as 71.8% of the video group had no ‘hands-off’ events when performing compression (vs 46.2% for the audio group, P = 0.02)Instructions from the dispatcher, along with a video demonstration of CPR, improved the time to initiate compression, the compression rate and the correct hand positioning. It also reduced the ‘hands-off’ events during CPR. However, emphasized instructions by video may be needed to increase. The depth of compressions
Peltan et al[15], 2022Multicenter randomized controlled trialThe telemedical consultant for intervention-groupNo-flow fraction did not differ between the 36 intervention groups (0.22-0.13) and the 35 control group (0.19-0.10) resuscitation simulations were included in the intention-to-treat analysis (P ¼, 41). The etiology of the simulated cardiac arrest was identified more often during evaluable resuscitations supported by a telemedical intensivist consultant (22/32, 69%) compared with control resuscitations [10/34 (29%); P ¼, .001], but other measures of resuscitation quality, resuscitation team performance, and participant experience did not differ between intervention groups. Problems with audio quality or telemedicine. Connection affected 14 intervention group resuscitations (39%)Consultation by a telemedical intensivist physician did not improve. Resuscitation quality during simulated ward-based IHCA
Lee et al[9], 2021Retrospective cohort studyAudio-instructed DA-CPRFavorable neurologic outcome was observed more in patients who received video-instructed DA-CPR (n = 75, 19.4%) than in patients who received audio-instructed DA-CPR (n = 117, 6.8%). The survival to discharge rate was also higher in video-instructed DA-CPR (n = 105, 27.1%) than audio-instructed DA-CPR (n = 211, 12.3%)Video-instructed DA-CPR was significant. Associated with neurologic recovery (aOR = 2.11, 95%CI: 1.48-3.01) and survival to discharge (aOR = 1.81, 95%CI: 1.33-2.46) compared to audio-instructed DA-CPR in adult OHCA patients after adjusting for age, gender, underlying diseases and CPR location. Video-instructed DA-CPR was associated with favorable outcomes in adult patients with OHCA in a metropolitan city equipped with sufficient experience and facilities
Sonkin et al[21], 2022A simulation studyParticipants communicated with the experimenter, presenting video clips showing patients that simulated three emergency scenarios: Trauma, an unresponsive patient with cardiac arrest, and an opiate overdoseThe trauma scenario was assessed most promptly, with instructions to handle the bleeding provided by all. Paramedics. In the unresponsive patient with cardiac arrest scenario, most of the participants achieved a correct initial. Diagnosis, and in the opiate overdose scenario, over half of the paramedics sought visual clinical clues for the differential. Diagnoses of loss of consciousness and their causes. Additional results show the type of assessment, treatment, and Diagnosis participants were provided in each scenario and their confidence about the situation. In the cardiac arrest scenario, the participants were assessed. the LOC in 41 (98%) sessions within a median of 1minute and 24 seconds (IQR: 00:41-02:33), evaluated breathing in 37 (88%) sessions within a median of 1 minute and 39 seconds (IQR: 00:54-03:14). The participants instructed the bystander to check central pulse in 10 (24%) sessions within a median of 3 minutes and 58 seconds (IQR: 03:06-05:20) - these participants were asked to measure the pulse only after the patient collapsed. Skin tone and sweating were assessed in 19 (45%) sessions within a median of 1 minute and 45 seconds (IQR: 01:06-02:28) and a list of the patient’s current Medications were requested in 10 (24%) sessions within a median of 2 minutes and 38 seconds (IQR: 01:25-03:17)The findings show that direct video communication between paramedics and the scene may facilitate correct diagnosis, provision of instructions for treatment, and early preparation of medications or equipment. These may decrease time to correct diagnosis and lifesaving treatment, and impact patient morbidity and mortality. Moreover, the findings highlight the differences between incidents with higher visual clarity, such as trauma and conditions. Require an extended diagnosis to reveal, such as unresponsive patients. This may also increase the paramedics’ mental preparedness for what is expected at the scene
Meinich-Bache et al[25], 2018A simulation studySmartphone video analysis in real-time is feasible for a range of conditions. With the use of a web-connected smartphone application which utilises the smartphone cameraFour experiments were performed to test the accuracy of the calculated chest compression rate. Under different conditions, a fifth experiment was done to test the accuracy of the CPR summary parameters TFSCR, TC, TWC, ACR, and NC. The average compression rate detection error was 2.7 compressions per minute (± 5.0 cpm), the calculated chest. The compression rate was within ± 10 cpm at 98% (± 5.5) of the time, and the average error of the summary CPR parameters was 4.5% (± 3.6)Real-time chest compression quality measurement by smartphone cameras are feasible for a range of bystanders, compression rates, camera positions, and noise conditions. (Is technology may be used to measure and improve the quality of telephone CPR and minimising hands-off times)
Kim et al[8], 2021Retrospective cohort studySALSA total of 616 consecutive out-of-hospital cardiopulmonary resuscitation cases in NHs were recorded, and 199 (32.3%) underwent SALS. Among the NH arrest patients, the survival discharge rate was a little higher in the SALS group than in the BLS group (4.0% vs 1.7%), but the difference was not significant (P = 0.078). Survival discharge with good neurologic outcome rates was 0.5% in the SALS group and 1.0% in the BLS group (P = 0.119). On the other hand, in the non-NH group, all outcome measures significantly improved when SALS was performed compared to BLS alone (survival discharge rate: 10.0% vs 7.3%, P = 0.001; good neurologic outcome: 6.8% vs 3.3%, Pb 0001)As a result of providing prehospital ACLS with direct medical intervention through remote video calls to paramedics, the survival to discharge rate and the good neurologic outcome (CPC 1, 2) of non-NH patients significantly improved; however, those of NH patients were not significantly increased
Linderoth et al[22], 2021Retrospective studyLive video of dispatcher-assisted CPRCPR was provided with live video streaming in 52 OHCA calls, with 90 bystanders who performed chest compressions. Hand position was incorrect for 38 bystanders (42.2%) and improved for 23 bystanders (60.5%) after video-instructed DA-CPR. The compression rate was incorrect for thirty-six bystanders (40.0%) and improved for 27 bystanders (75.0%). Compression depth was incorrect for 57 bystanders (63.3%) and enhanced for 33 bystanders (57.9%). The adjusted odds ratios for improved CPR after video-instructed DA-CPR were hand position 5.8 (95%CI: 2.8-12.1), compression rate 77 (95%CI: 3.4-17.3), and compression depth 7.1 (95%CI: 3.9-12.9). Hands-o time was reduced for 34Live video streaming from the scene of a cardiac arrest to medical dispatchers is feasible. It allowed an opportunity for dispatchers to coach those providing CPR, which was associated with a subjectively evaluated improvement in CPR performance
Ofoma et al[26], 2022A prospective, voluntary, multi-site registry of IHCATelemedicine critical care14373 (32.2%) participants suffered IHCA at hospitals with TCC, and 27032 (60.6%) occurred in an ICU. There was no difference between TCC and non-TCC hospitals in acute resuscitation survival rate or survival to discharge rates for either IHCA occurring in the ICU (acute survival OR = 1.02; 95%CI: 0.92-1.15; survival to discharge OR = 0.94; 95%CI: 0.83-1.07) or outside of the ICU (acute survival OR = 1.03; 95%CI: 0.91-1.17); survival to discharge (OR = 0.99; 95%CI: 0.86-1.12). Timing of cardiac arrest did not modify the association between TCC availability and acute resuscitation survival (P = 0.37 for interaction) or survival to discharge (P = 0.39 for interaction)Hospital availability of TCC was not associated with improved outcomes for in-hospital cardiac arrest
Plata et al[18], 2021Randomised controlled simulation trialTelemedicineNo-flow fraction did not differ between the 36 intervention group (0.22-0.13) and the 35 control group (0.19-0.10) resuscitation simulations included in the intention-to treat analysis (P ¼ .41). The etiology of the simulated cardiac arrest was identified more often during evaluable resuscitations supported by a telemedical intensivist consultant (22/32, 69%) compared with control resuscitations [10/34 (29%); P ¼ .001], but other measures of resuscitation quality, resuscitation team performance, and participant experience did not differ between intervention groups. Problems with audio quality or the telemedicine connection affected 14 intervention group resuscitations (39%)Consultation by a telemedical intensivist physician did not improve resuscitation quality during simulated ward-based IHCA
Lee et al[27], 2021Randomised controlled simulation trialVideo call-based DACPR (V-DACPR) compared to conventional DACPRThe simulation results of 131 volunteers were analysed. The mean proportion of adequate hand positioning was highest in V-DACPR with rapid transition (V-DACPR with rapid transition vs C-DACPR: 92.7% vs 82.4%, P = 0.03). The mean chest compression depth was deeper in both V-DACPR groups than in the C-DACPR group (V-DACPR with rapid transition vs C-DACPR: 40.7 mm vs 35.9 mm, P = 0.01, V-DACPR with delayed transition vs C- DACPR: 40.9 mm vs 35.9 mm, P = 0.01). Improvement in the proportion of adequate hand positioning was observed in the V-DACPR groups (r = 0.25, P < 0.01 for rapid transition and r = 0.19, P < 0.01 for delayed transition)Participants in the V-DACPR groups performed higher quality chest compression with higher appropriate hand positioning and deeper compression depth than the C-DACPR group
Aranda-García et al[16], 2023Randomised controlled simulation trialA SG-VA intervention group or a SP-AA control groupNine of the 14 SG-VA rescuers correctly completed the BLS protocol compared with none of the SP-AA rescuers (P = 0.01). A significantly higher number of SG-VA rescuers successfully opened the airway (13 vs 5, P = 0.002), checked breathing (13 vs 8, P = 0.03), correctly positioned the automatic external defibrillator pads (14 vs 6, P = 0.001), and warned bystanders to stay clear before delivering the shock (12 vs 0, P < 0.001). No significant differences were observed for performance times or chest compression quality. The mean compression rate was 104 compressions per minute in the SG-VA group and 98 in the SP-AA group (P = 0.46); the mean compression depth was 4.5 cm and 4.4 cm (P = 0.49), respectivelySmart glasses could significantly improve dispatcher-assisted bystander performance in an OHCA event. Their potential in real-life situations should be evaluated
Pérez Alonso et al[14], 2017Randomised clinical simulationGG/controlThirty-six nurses were enrolled in each study group. Statistically significant differences were found in the percentages of successful defibrillation (100% GG vs 78% control; P = 0005) and CPR completion times: 213.91 seconds for GG and 250.31 seconds for control (average difference = 36.39 seconds (95%CI: 12.03-60.75), P = 0.004)Telematics support by an expert through GG improves success rates and completion times while performing CPR in simulated clinical situations for nurses in simulated scenarios
Lee et al[28], 2020Retrospective cohortAudio-instructed DA-CPR vs video-instructed DA-CPRA total of 1720 eligible OHCA patients (1489 and 231 in the audio and video groups, respectively) were evaluated. The median ITI was 136 seconds in the audio group and 122 seconds in the video group (P = 0.12). The survival to discharge rates were 89% in the audio group and 14.3% in the video group (P < 0.01). Good neurological outcomes occurred in 5.8% and 10.4% of the audio and video groups, respectively (P < 0.01). Compared to the audio group, the AORs (95%CIs) for survival to discharge, good neurological outcome, and early ITI of the video group were 120 (0.741, 94), 1.28 (0.732, 26) and 1.00 (0.701, 43), respectively. The PSM population showed results similar to those of the original cohortCompared to audio-instructed DA-CPR, video-instructed DA-CPR was not associated with survival improvement in this observational study conducted in one metropolitan city. Randomised controlled trials are needed to compare the effects of video- and audio-instructed DA-CPR
Ecker et al[35], 2021Prospective randomised pilotA video live stream from the caller’s smartphone to the EMS dispatch centre-This study shows that V-CPR is feasible using a video livestream from a smartphone and that typical resuscitation mistakes (which would lead to low-quality CPR) can be detected and corrected by the EMS dispatcher. Moreover, specific training of dispatchers could become necessary to achieve the best results in V-CPR
Yang et al[29], 2009Randomised controlled studyVideo cell phone with both voice and video modesThe quality of CPR was evaluated by reviewing the videos and mannequin reports. Chest compressions among the video group were faster (median rate 955 vs 63.0 minutes, P < 0.01), deeper (median depth 36.0 vs 25.0 mm, P < 0.01), and of more appropriate depth (20.0% vs 0%, P < 0.01). The video group had more “hands-off” time (5.0 vs 0 seconds, P < 0.01), longer time to first chest compression (145.0 vs 116.0 seconds, P < 0.01) and total instruction time (150.0 vs 121.0 seconds, P < 0.01)The quality of CPR was evaluated by reviewing the videos and mannequin reports. Chest compressions among the video group were faster (median rate 955 vs 63.0 minutes, P < 0.01), deeper (median depth 36.0 mm vs 25.0 mm, P < 0.01), and of more appropriate depth (20.0% vs 0%, P < 0.01). The video group had more “hands-off” time (5.0 seconds vs 0 seconds, P < 0.01), longer time to first chest compression (145.0 seconds vs 116.0 seconds, P < 0.01) and total instruction time (150.0 seconds vs 121.0 seconds, P < 0.01)
Morand et al[30], 2023NRLive video toolsThe first study’s results show that dispatchers are interested in visualising the scene with live video and broadcasting a live demonstration video when possible. The initial results also show that collaboration within the community is enhanced by the shared simulation and debriefing experiences, clarifying regulation procedures, and improving communication. Finally, an iterative development based on the lessons learned, expectations, and constraints of each previous study promotes the existence of a living lab that aims to determine the place of live video tools in the sequence of care performed by dispatchersLiving labs offer the opportunity to grasp previously undetected insights and redefine the use of the applications while potentially developing a sense of community among the stakeholders
You et al[31], 2008A prospective observational studyVideo telephonyPlacement of the electrode pads was performed correctly by all 52 participants, and 51 (98%) delivered an accurate shock. The mean (SD) time to correct shock delivery was 131.8 (20.6) seconds (range: 101-202)Correct pad placement and shock delivery can be performed using an AED when instructions are provided via video telephone because a dispatcher can monitor every step and provide correct information
Barcala et al[17], 2023Descriptive and comparative designSGsReliability was analysed by comparing the assessment of variables performed by the dispatcher through SGs with those registered by an on-scene instructor. Assistance through SGs was needed in 72% of the BLS steps, which enabled all participants to perform the ABC approach and use AED correctly. Feasibility was proven that the dispatcher’s feedback through SGs helped to improve bystanders’ performance, as after the dispatcher gave feedback via SGs, only 3% of skills were incorrect. Comparison of on-scene instructor vs SGs assessment by dispatcher differ in 8% of the analysed skills: Most significant difference in the “incorrect hand position during CPR” (on-scene: 33% vs dispatcher: 0%). When comparing the 1st minute with the 2nd minute, there were only significant differences in the percentage of compressions with correct depth (1st: 48 ± 42%, 2nd: 70 ± 31, P = 0.02)Using SGs in aquatic settings seems feasible if the right wireless connectivity conditions are available. Communication between the emergency dispatcher and the witness is seamless and is especially helpful during the dispatch of the ABC approach and AED use. The small sample size did not allow us to investigate significant differences in CPR-quality markers. We consider that these devices have great potential for communication between dispatchers and laypersons but need improvement to be used in real emergencies
Bolle et al[7], 2011Randomised controlled trialVideo calls or via ordinary mobile phone callsEach student answered a questionnaire to assess the technology’s understanding, confidence and usefulness. The mean age was 17.3 years in the video group and 17.9 years in the audio group. There were 27% male participants in the video group and 34% male participants in the audio group. Seventy-three per cent of the students in the video group and 71% in the audio group reported previous cardiopulmonary resuscitation trainingAudio-visual communication during dispatch-assisted cardiopulmonary resuscitation improved rescuers’ confidence in this study of simulated cardiac arrest. The sound quality may be a problem with current video mobile calls, but users prefer video communication despite low-quality images. The use of audio-visual communication between lay bystanders and dispatchers has the potential to improve the quality of human interaction and, thus, the quality of pre-hospital resuscitation
Bang et al[32], 2020Prospective randomised simulationVideocall assist laypersonsThere was no significant difference among the three groups regarding baseline characteristics. Performance scores in the checklist for using AED were higher in the mobile video call-guided group, especially in the “power on AED” and “correctly attaches pads” categories, than in the other groups. However, the time interval to defibrillation was significantly longer in the mobile video call-guided group. Conclusions. Mobile video call guidance might be an alternative method to facilitate AED use by laypersons. Therefore, further well-designed research is needed to evaluate the feasibility of this approach in OHCAIn summary, this simulation evaluation confirmed that the AED performance of the laypersons improved in the video call-guided group than in the control or voice call-guided group. When using an AED alone, the AED could not be turned on quickly, and the pad could not be appropriately placed; therefore, a video call could be considered a feasible alternative in layperson CPR for OHCA
Bolle et al[33], 2009Clinical trialThe median CPR time without chest compression (“hands-off time”) was shorter in the video-call group vs the audio-call group (303 vs 331 seconds; P 5 0.048), but the median time to first compression was not shorter (104 vs 102 seconds; P 5 0.29). The median time to first ventilation was insignificantly shorter in the video-call group (176 vs 205 seconds; P 5 0.16). This group also had a slightly higher proportion of ventilation without error (0.11 vs 0.06; P 5 0.30)Video calls or audio calls with experienced nurse dispatchersVideo communication is unlikely to improve T-CPR significantly without proper training of dispatchers and when using dispatch protocols written for audio-only calls. Improved dispatch procedures and training for handling video calls require further investigation
Kim et al[8], 2021Mixed method designVideo instructions vs audio instructionVideo-based instruction was found to be more effective in the number of chest compressions (P < 0.01), chest compression rate (P < 0.01), and chest compression interruptions (P < 0.01). The accuracy of the video group for the chest compression region was high (P = 0.05). Participants’ experiences were divided into three categories: ‘‘unfamiliar but beneficial experience’’, ‘‘met helper during a desperate and embarrassing situation’’, and ‘‘diverse views on drone use”This study examined the impact of audio and video CPR instructions provided by dispatchers when an automatic defibrillator is delivered via drone during a cardiac arrest scenario outside a hospital. The research revealed significant differences between the audio and video instruction groups in various aspects of CPR performance, including chest compressions, compression rate, and hands-off time. Additionally, differences were observed in factors such as compression location, hand shape, and posture, indicating variations in CPR accuracy. Participants reported three main categories of experiences: Finding unfamiliar but helpful drone assistance, encountering assistance in a challenging situation, and having diverse opinions on drone use. These findings offer valuable insights for developing emergency medical services utilising drones and formulating video-instruction guidelines for dispatchers
Yuksen et al[23], 2016Retrospective studyVideo instruction vs on-scene medical instructionFourteen representative teams, 14 physicians, 14 nurses, and 28 emergency medicine technicians, participated in the study. The average ages of participants in all three occupations were between the second and third decade of life. The percentages of participants with more than three years of ambulance experience were 71%, 64.3%, and 53.6% in the physicians, nurses, and EMTs groups. The median times of all outcomes were significantly longer in the online group than the on-scene group, including times from start to chest compression (total 102 seconds vs 36 seconds), full times from the beginning to VT/VF detection (187 seconds vs 99 seconds); times from VT/VF detection to the first defibrillation (57 seconds vs 28 seconds); and times from the start of adrenaline injection (282 seconds vs 165 seconds). The percentages of using amiodarone (21.43% vs 57.14%; P value < 0.001), establishment of a definitive airway (35.71% vs 100%; P value = 0.003), and correct detections of PEA (28.57% vs 100%; P value < 0.001) were significantly lower in the online group than the on-scene group. The high-quality CPR outcomes between the online and on-scene groups were comparableOnline medical instruction may have worse CPR outcomes compared with on-scene medical instruction in shockable, simulated CPR scenarios. Further studies are needed to confirm these results
Lee et al[34], 2018Randomised trialVideo call guidanceThe median value of the time to the first defibrillation was significantly shorter in the video call guidance group (56 seconds) than in the conventional group. Group (73 seconds) (P < 0.001). The median value of the total hands-of time was also significantly shorter (228 seconds vs 285.5 seconds) (P < 0.001), the hands-of ratio, defined as the proportion of hands-of time out of the total CPR time, was significantly shorter in the Video call guidance group (0.32 vs 0.41) (P < 0.001)Physician-guided CPR with a video call enabled prompt manual defibrillation and significantly shortened the time required for first defibrillation, hands-of-time, and hands-of ratio in simulated cases of prehospital cardiac arrest
IHCA: In-hospital cardiac arrest; NR: Not reported; CPR: Cardiopulmonary resuscitation; LOC: Level of consciousness; V-CPR: Video-assisted cardiopulmonary resuscitation; T-CPR: Telephone-assisted cardiopulmonary resuscitation; DA-CPR: Dispatcher-assisted cardiopulmonary resuscitation; OHCA: Out-of-hospital cardiac arrest; IQR: Interquartile range; TFSCR: Time to first stable compression rate; TC: Active compression time; TWC: Hands-off time; NC: Number of compressions; NH: Nursing homes; ACR: Average compression rate; SALS: Smartphone-based advanced cardiac life support; CPC: Cereberal performance category; TCC: Telemedicine critical care; OR: Odds ratio; CI: Confidence interval; ICU: Intensive care unit; V-DACPR: Video dispatcher-assisted cardiopulmonary resuscitation; C-DACPR: Called dispatcher assisted cardiopulmonary resuscitation; GC: Google glasses; SG-VA: Smart glasses-video assistance; SP-AA: Smartphone-audio assistance; BLS: Basic life support; AOR: Adjusted odds ratio; EMS: Emergency medical services; ITI: Time from call to initiation; PSM: Propensity score matching; AED: Automated external defibrillator; SD: Standard deviation; SGs: Smart glasses; VT/VF: Ventricular tachycardia/Ventricular fibrillation; PEA: Pulseless electrical activity.