key: cord-1033822-4pngs9ic
authors: Bielski, Karol; Szarpak, Agnieszka; Jaguszewski, Miłosz Jaroslaw; Kopiec, Tomasz; Smereka, Jacek; Gasecka, Aleksandra; Wolak, Przemysław; Nowak-Starz, Grazyna; Chmielewski, Jaroslaw; Rafique, Zubaid; Peacock, Frank William; Szarpak, Lukasz
title: The Influence of COVID-19 on Out-Hospital Cardiac Arrest Survival Outcomes: An Updated Systematic Review and Meta-Analysis
date: 2021-11-27
journal: J Clin Med
DOI: 10.3390/jcm10235573
sha: 3a6975cb16d09f16e844a336303098a6cd3e2438
doc_id: 1033822
cord_uid: 4pngs9ic

Cardiopulmonary resuscitation in patients with out-of-hospital cardiac arrest (OHCA) is associated with poor prognosis. Because the COVID-19 pandemic may have impacted mortality and morbidity, both on an individual level and the health care system as a whole, our purpose was to determine rates of OHCA survival since the onset of the SARS-CoV2 pandemic. We conducted a systematic review and meta-analysis to evaluate the influence of COVID-19 on OHCA survival outcomes according to the PRISMA guidelines. We searched the literature using PubMed, Scopus, Web of Science and Cochrane Central Register for Controlled Trials databases from inception to September 2021 and identified 1775 potentially relevant studies, of which thirty-one articles totaling 88,188 patients were included in this meta-analysis. Prehospital return of spontaneous circulation (ROSC) in pre-COVID-19 and COVID-19 periods was 12.3% vs. 8.9%, respectively (OR = 1.40; 95%CI: 1.06–1.87; p < 0.001). Survival to hospital discharge in pre- vs. intra-COVID-19 periods was 11.5% vs. 8.2% (OR = 1.57; 95%CI: 1.37–1.79; p < 0.001). A similar dependency was observed in the case of survival to hospital discharge with the Cerebral Performance Category (CPC) 1–2 (6.7% vs. 4.0%; OR = 1.71; 95%CI: 1.35–2.15; p < 0.001), as well as in the 30-day survival rate (9.2% vs. 6.4%; OR = 1.63; 95%CI: 1.13–2.36; p = 0.009). In conclusion, prognosis of OHCA is usually poor and even worse during COVID-19.

The COVID-19 pandemic has negatively impacted health systems around the world and adversely affected cardiopulmonary resuscitation of out-of-hospital cardiac arrests (OHCA) [1, 2] . As of 27 October 2021, more than 244 million cases of COVID-19 have been identified worldwide, with the number of deaths exceeding 4.9 million. Although most patients with COVID-19 recover without extensive intervention, a minority require intensive cardiac and respiratory support, ranging from oxygen therapy to extracorporeal membrane oxygenation [3] .

The risk of exposure to SARS-CoV-2 infection to medical personnel, as well as those administering first aid during cardiac arrest, poses a challenge [4] [5] [6] . Until the widespread introduction of a vaccination program for medical personnel, this risk was of paramount concern. Although the risk is lower after the recent availability of effective COVID-19 vaccines, the lack of complete postvaccination protection and the emergence of new variants have made it necessary to alter protocols and provide protective equipment to medical personnel on an ongoing basis [7] . Many institutions and scientific societies have thus modified resuscitation protocols where the avoidance of invasive ventilation is preferred to protect medical staff [8] . Others have proposed an early termination of resuscitation in patients with COVID-19 [9] .

These changes may have contributed to the recently increased number of out-ofhospital sudden cardiac arrest cases [3] . The reason for the increased number of cases is not only due to severe respiratory failure but also cardiac and vascular complications during and after infection [5] . Ultimately, cardiopulmonary resuscitation in patients with OHCA is associated with poor prognosis, and the COVID-19 pandemic may have worsened morbidity and mortality by impacting individual health and by crowding the healthcare system [9] [10] [11] [12] . Critically ill COVID-19 patients may experience cardiac arrest, not only during acute hospitalization but also during rehabilitation and postrecovery periods [13] .

Our previously published meta-analysis [14] suggests that suspicion or diagnosis of COVID-19 at OHCA is associated with a lower rate of shockable rhythms and a reduced survival to hospital discharge (SHD) rate. As there has been a tremendous amount of data reported since our prior publication, we performed an updated systematic review of the literature and meta-analysis to evaluate the influence of COVID-19 on OHCA survival outcomes.

This manuscript was prepared following the recommendations of the Preferred Reported Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines [15] (Table S3) . A protocol of this meta-analysis has not been registered.

Before commencing the study, all reviewers agreed on the analysis methods and the inclusion and exclusion criteria to be used. Two reviewers (K.B. and M.P.) independently performed a comprehensive literature search using PubMed, Scopus, Web of Science and Cochrane Central Register for Controlled Trials databases. The most recent search was performed on 10 October 2021. The search was conducted using the terms: "COVID-19" OR "SARS-CoV-2" AND "heart arrest" OR "cardiac arrest" OR "circulation arrest" OR "out-hospital cardiac arrest" OR "OHCA" OR "CA" OR "resuscitation" OR "CPR" OR "return of spontaneous circulation" OR "ROSC" OR "pulseless electrical activity" OR "asysto *" OR "pulseless ventric * tachycardia" OR "heart ventric * fibrillation" OR "cardiac ventric * fibrillation". Additionally, a manual search of references listed in retrieved articles and reviews was also performed. All references were saved in an EndNote (End Note, Inc., Philadelphia, PA, USA) library used to identify the duplicates.

Studies included in this meta-analysis met the following PICOS criteria: (1) Participants: patients >18 years of age with out-of-hospital cardiac arrest due to any cause;

(2) Intervention: cardiac arrest in COVID-19 period: (3) Comparison: cardiac arrest in pre-COVID-19 period; (4) Outcomes: detailed information for survival; (5) Study Design: randomized controlled trials, quasirandomized or observational studies comparing cardiac arrest during and before the COVID-19 period for their effects in patients with cardiac arrest. Finally, we excluded papers not containing comparator groups, conference or poster papers, reviews, case reports or articles not containing original data.

Two reviewers (K.B. and J.C.) independently extracted data from each article that met the inclusion criteria. Disagreements among the authors regarding values or analysis assignments were resolved through discussion with the third reviewer (L.S.). Reviewers were careful to avoid the inclusion of data from duplicate publications. The data extracted from each study included the (1) study characteristics (i.e., first author's name, year of publication, study location, study design, inclusion and exclusion criteria, primary findings); (2) participant characteristics in each group (i.e., number of participants, age, sex, comorbidities); (3) survival outcomes (i.e., the return of spontaneous circulation, survival to hospital admission with spontaneous circulation (SHA), survival to hospital discharge or survival to hospital discharge with good neurological outcome defined as 1 or 2 grade in Cerebral Performance Categories Scale).

We evaluated the following outcomes in our analysis, based on consensus among the content experts in our group, regarding important outcomes. The primary outcome was survival to hospital discharge (SHD), or 30 days, whichever came first. Secondary outcomes were the return of spontaneous circulation (ROSC), recurrence of cardiac arrest, survival with favorable neurologic status (defined as survival with Cerebral Performance Category (CPC) 1 or 2) and CPR parameters (i.e., bystander witnessed, bystander CPR).

A systematic assessment of bias in the included studies was performed using the Cochrane criteria [16, 17] . For this purpose, a tool for Risk of Bias in Non-randomized Studies-of Interventions (ROBINS-I) [18] was used. ROBINS-I examines 7 domains of bias due to: (1) confounding; (2) selection of participants; (3) the classification of interventions; (4) deviations from intended interventions; (5) missing data; (6) measurement of outcomes; and (7) the selection of the reported result. The overall ROBINS-I judgment at the domain and study levels was attributed according to the criteria specified in the ROBVIS tool [19] . The risk of bias (RoB) was performed independently by two reviewers (T.K. and K.B.); disagreements were resolved by a third reviewer (L.S.) if necessary.

The Mantel-Haenszel method was used to analyze dichotomous outcomes, and results are reported as odds ratios (ORs) or risk ratios (RRs) with a 95% confidence interval (CI). Continuous outcome differences were analyzed using an inverse variance model with a 95% CI, and values are reported as mean difference (MD). When the continuous outcome was reported in a study as median, range and interquartile range, we estimated means and standard deviations using the formula described by Hozo et al. [16] .

We quantified heterogeneity in each analysis by the tau-squared and I-squared statistics. Heterogeneity was detected with the chi-squared test with n-1 degree of freedom, which was expressed as I 2 . Values of I 2 > 50% and >75% were considered to indicate moderate and significant heterogeneity among studies, respectively. A random-effects model was used to pool study results independently of the p-value for heterogeneity or I 2 [20] .

All p-values were two-tailed and considered significant if p < 0.05. Statistical analysis was performed using Review Manager (ver. 5.4, Nordic Cochrane Centre, The Cochrane Collaboration, Copenhagen, Denmark). To evaluate the potential for publication bias, we plotted values against associated standard errors [21] and used Begg's test to assess the symmetry of the resulting funnel plot [22] . We considered publication bias to be present at p < 0.1 in the asymmetry test. However, when a limited number of studies (<10) were included in the analysis, publication bias was not evaluated.

We searched 1775 potentially relevant studies in the databases (PubMed, Scopus, Web of Science and Cochrane Central). After excluding 668 duplicates, 1107 studies were screened using titles and abstracts; of those, 1062 studies were excluded. After fulltext assessment for eligibility, 14 were excluded because they did not meet the inclusion criteria. Finally, thirty-one articles, including 88,188 patients, were included in this metaanalysis . A flow diagram showing stages of database search and study selection is shown in Figure 1 .

We quantified heterogeneity in each analysis by the tau-squared and I-squared statistics. Heterogeneity was detected with the chi-squared test with n-1 degree of freedom, which was expressed as I 2 . Values of I 2 > 50% and >75% were considered to indicate moderate and significant heterogeneity among studies, respectively. A random-effects model was used to pool study results independently of the p-value for heterogeneity or I 2 [20] . All p-values were two-tailed and considered significant if p < 0.05. Statistical analysis was performed using Review Manager (ver. 5.4, Nordic Cochrane Centre, The Cochrane Collaboration, Copenhagen, Denmark). To evaluate the potential for publication bias, we plotted values against associated standard errors [21] and used Begg's test to assess the symmetry of the resulting funnel plot [22] . We considered publication bias to be present at p < 0.1 in the asymmetry test. However, when a limited number of studies (<10) were included in the analysis, publication bias was not evaluated.

We searched 1775 potentially relevant studies in the databases (PubMed, Scopus, Web of Science and Cochrane Central). After excluding 668 duplicates, 1107 studies were screened using titles and abstracts; of those, 1062 studies were excluded. After full-text assessment for eligibility, 14 were excluded because they did not meet the inclusion criteria. Finally, thirty-one articles, including 88,188 patients, were included in this meta-analysis . A flow diagram showing stages of database search and study selection is shown in Figure 1 . Twenty-seven studies reported OHCA outcomes in pre-vs. intra-COVID-19 periods [23, 24, [26] [27] [28] [29] 31, 33, 35, [37] [38] [39] [40] [41] [42] [44] [45] [46] [47] [48] [49] [50] [51] [52] [53] , and OHCA outcomes in SARS-CoV-2-positive vs. -negative patients were reported in seven trials [25, 30, 32, 34, 36, 43, 51] . Characteristics of the individual studies are presented in Tables S1 and S2. The mean age of patients suffering from OHCA in the pre-COVID-19 period was 66.0 ± 17.3 years compared to 67.8 ± 17.1 years for patients since the COVID-19 pandemic.

The Cochrane risk of bias of the included studies is shown in Figures S1 and S2. The overall risk of bias was judged as low in twenty-nine studies [23] [24] [25] [26] [27] [28] [29] [30] [31] [32] [34] [35] [36] [37] [38] [39] [40] [41] [42] [43] [44] [45] [46] [48] [49] [50] [51] [52] [53] , and reviewers indicate some concerns on the other two [33, 47] .

Overall, the time to EMS arrival on the scene, reported in 18 studies, was 9.1 ± 2.1 min in the pre-COVID-19 period versus 9.8 ± 2.6 min (MD = −1.05; 95%CI: −1.54 to −0.56; p < 0.001) since the COVID-19 pandemic began ( Figure 2 ).

Twenty-seven studies reported OHCA outcomes in pre-vs. intra-COVID-19 periods [23, 24, [26] [27] [28] [29] 31, 33, 35, [37] [38] [39] [40] [41] [42] [44] [45] [46] [47] [48] [49] [50] [51] [52] [53] , and OHCA outcomes in SARS-CoV-2-positive vs. -negative patients were reported in seven trials [25, 30, 32, 34, 36, 43, 51] . Characteristics of the individual studies are presented in Tables S1 and S2. The mean age of patients suffering from OHCA in the pre-COVID-19 period was 66.0 ± 17.3 years compared to 67.8 ± 17.1 years for patients since the COVID-19 pandemic.

The Cochrane risk of bias of the included studies is shown in Figures S1 and S2. The overall risk of bias was judged as low in twenty-nine studies [23] [24] [25] [26] [27] [28] [29] [30] [31] [32] [34] [35] [36] [37] [38] [39] [40] [41] [42] [43] [44] [45] [46] [48] [49] [50] [51] [52] [53] , and reviewers indicate some concerns on the other two [33, 47] .

Overall, the time to EMS arrival on the scene, reported in 18 studies, was 9.1 ± 2.1 min in the pre-COVID-19 period versus 9.8 ± 2.6 min (MD = −1.05; 95%CI: −1.54 to -0.56; p < 0.001) since the COVID-19 pandemic began ( Figure 2 ). Shockable initial rhythms were observed in 16.7% of OHCA in the pre-COVID-19 period compared to 12.4% since the COVID-19 pandemic began (OR = 1.17; 95%CI: 1.03 to 1.32; p < 0.001; Figure 3 ).

Twenty-seven studies reported OHCA outcomes in pre-vs. intra-COVID-19 periods [23, 24, [26] [27] [28] [29] 31, 33, 35, [37] [38] [39] [40] [41] [42] [44] [45] [46] [47] [48] [49] [50] [51] [52] [53] , and OHCA outcomes in SARS-CoV-2-positive vs. -negative patients were reported in seven trials [25, 30, 32, 34, 36, 43, 51] . Characteristics of the individual studies are presented in Tables S1 and S2. The mean age of patients suffering from OHCA in the pre-COVID-19 period was 66.0 ± 17.3 years compared to 67.8 ± 17.1 years for patients since the COVID-19 pandemic.

The Cochrane risk of bias of the included studies is shown in Figures S1 and S2 . The overall risk of bias was judged as low in twenty-nine studies [23] [24] [25] [26] [27] [28] [29] [30] [31] [32] [34] [35] [36] [37] [38] [39] [40] [41] [42] [43] [44] [45] [46] [48] [49] [50] [51] [52] [53] , and reviewers indicate some concerns on the other two [33, 47] .

Overall, the time to EMS arrival on the scene, reported in 18 studies, was 9.1 ± 2.1 min in the pre-COVID-19 period versus 9.8 ± 2.6 min (MD = −1.05; 95%CI: −1.54 to -0.56; p < 0.001) since the COVID-19 pandemic began ( Figure 2 ). Pooled analysis of resuscitation outcomes are presented in Table 1 . There was no significant difference between pre-COVID-19 and COVID-19 periods in bystander-witnessed arrests, bystander CPR, use of mechanical chest compression or use of targeted temperature management (p > 0.05). However, since the COVID-19 pandemic began, endotracheal intubation was utilized more frequently during resuscitation (OR = 1.91; 95%CI: 1.37 to 2.68; p < 0.001), cardiac arrest was observed more frequent at home (OR = 0.74; 95%CI: 0.65 to 0.84; p < 0.001) and bystanders used AED less frequently (OR = 1.35; 95%CI: 1.25 to 1.46; p < 0.001). A visual examination of the funnel plots did not reveal relevant asymmetry consistent with publication bias (Figures S3 and S4 ).

Six studies [31, 38, 44, 48, 53] reported prehospital ROSC in pre-COVID-19 and COVID-19 periods with a variance of 12.3% vs. 8.9% (OR = 1.40; 95%CI: 1.06 to 1.87; p < 0.001; Figure 4 ), respectively. Pooled analysis of resuscitation outcomes are presented in Table 1 . There was no significant difference between pre-COVID-19 and COVID-19 periods in bystander-witnessed arrests, bystander CPR, use of mechanical chest compression or use of targeted temperature management (p > 0.05). However, since the COVID-19 pandemic began, endotracheal intubation was utilized more frequently during resuscitation (OR = 1.91; 95%CI: 1.37 to 2.68; p < 0.001), cardiac arrest was observed more frequent at home (OR = 0.74; 95%CI: 0.65 to 0.84; p < 0.001) and bystanders used AED less frequently (OR = 1.35; 95%CI: 1.25 to 1.46; p < 0.001). A visual examination of the funnel plots did not reveal relevant asymmetry consistent with publication bias (Figures S3 and S4 ).

Six studies [31, 38, 44, 48, 53] reported prehospital ROSC in pre-COVID-19 and COVID-19 periods with a variance of 12.3% vs. 8.9% (OR = 1.40; 95%CI: 1.06 to 1.87; p < 0.001; Figure 4 ), respectively. Survival to hospital admission with spontaneous circulation was reported in 12 studies and was significantly higher in the pre-COVID-19 period compared to the COVID-19 period (28.4% vs. 19.3%, respectively; OR = 1.76; 95%CI: 1.44 to 2.14; p < 0.001; Figure 5 ). Survival to hospital admission with spontaneous circulation was reported in 12 studies and was significantly higher in the pre-COVID-19 period compared to the COVID-19 period (28.4% vs. 19.3%, respectively; OR = 1.76; 95%CI: 1.44 to 2.14; p < 0.001; Figure 5 ). Fifteen studies reported survival to hospital discharge. Pooled analysis of SHD was 11.5% in OHCA patients in the pre-COVID-19 period compared to 8.2% during the COVID-19 period (OR = 1.57; 95%CI: 1.37 to 1.79; p < 0.001; Figure 6 ). A funnel plot and Egger's regression test were employed to examine publication bias ( Figure S5 ). Survival to hospital discharge with CPC 1-2 was reported in six studies and was 6.7% vs. 4.0% for pre-COVID-19 and during the COVID-19 periods (OR = 1.71; 95%CI: 1.35 to 2.15; p < 0.001; Figure 7) . Moreover, six studies reported a 30-day survival rate in pre-COVID-19 and COVID-19 periods with a variance of 9.2% vs. 6.4%, respectively (OR = 1.63; 95%CI: 1.13 to 2.36; p = 0.009; Figure 8) . A visual examination of the funnel plots did not reveal relevant asymmetry consistent with publication bias ( Figure S6 ).

Seven studies showed survival outcomes in during the pandemic among patients with and without SARS-CoV-2 infection [25, 30, 32, 34, 36, 43, 51] . Pooled analysis of ROSC in SARS-CoV-2 positive vs. negative patients was 22.9% vs. 28 Fifteen studies reported survival to hospital discharge. Pooled analysis of SHD was 11.5% in OHCA patients in the pre-COVID-19 period compared to 8.2% during the COVID-19 period (OR = 1.57; 95%CI: 1.37 to 1.79; p < 0.001; Figure 6 ). A funnel plot and Egger's regression test were employed to examine publication bias ( Figure S5 ). Survival to hospital admission with spontaneous circulation was reported in 12 studies and was significantly higher in the pre-COVID-19 period compared to the COVID-19 period (28.4% vs. 19.3%, respectively; OR = 1.76; 95%CI: 1.44 to 2.14; p < 0.001; Figure 5 ). Fifteen studies reported survival to hospital discharge. Pooled analysis of SHD was 11.5% in OHCA patients in the pre-COVID-19 period compared to 8.2% during the COVID-19 period (OR = 1.57; 95%CI: 1.37 to 1.79; p < 0.001; Figure 6 ). A funnel plot and Egger's regression test were employed to examine publication bias ( Figure S5 ). Survival to hospital discharge with CPC 1-2 was reported in six studies and was 6.7% vs. 4.0% for pre-COVID-19 and during the COVID-19 periods (OR = 1.71; 95%CI: 1.35 to 2.15; p < 0.001; Figure 7) . Moreover, six studies reported a 30-day survival rate in pre-COVID-19 and COVID-19 periods with a variance of 9.2% vs. 6.4%, respectively (OR = 1.63; 95%CI: 1.13 to 2.36; p = 0.009; Figure 8) . A visual examination of the funnel plots did not reveal relevant asymmetry consistent with publication bias ( Figure S6 ).

Seven studies showed survival outcomes in during the pandemic among patients with and without SARS-CoV-2 infection [25, 30, 32, 34, 36, 43, 51] . Pooled analysis of ROSC in SARS-CoV-2 positive vs. negative patients was 22.9% vs. 28 Survival to hospital discharge with CPC 1-2 was reported in six studies and was 6.7% vs. 4.0% for pre-COVID-19 and during the COVID-19 periods (OR = 1.71; 95%CI: 1.35 to 2.15; p < 0.001; Figure 7) . Moreover, six studies reported a 30-day survival rate in pre-COVID-19 and COVID-19 periods with a variance of 9.2% vs. 6.4%, respectively (OR = 1.63; 95%CI: 1.13 to 2.36; p = 0.009; Figure 8) . A visual examination of the funnel plots did not reveal relevant asymmetry consistent with publication bias ( Figure S6 ).

Seven studies showed survival outcomes in during the pandemic among patients with and without SARS-CoV-2 infection [25, 30, 32, 34, 36, 43, 51] . Pooled analysis of ROSC in SARS-CoV-2 positive vs. negative patients was 22.9% vs. 28.3%, respectively (OR = 0.69; 95%CI: 0.52 to 0.92; p = 0.01; Table 2 ). A similar relationship was observed in both survival to hospital admission (8.8% vs. 18.5%; OR = 0.44; 95%CI: 0.22 to 0.88; p = 0.02), as well as in the 30-day survival ratio (0.7% vs. 4.2%; OR = 0.12; 95%CI: 0.05 to 0.31; p < 0.001). There were no significant differences between SARS-CoV-2-positive and -negative patients in the context of survival to hospital discharge (1.7% vs. 4.2%; OR = 0.98; 95%CI: 0.25 to 3.83; p = 0.97), as well as in survival to hospital discharge with CPC 1 or 2 (11.1% vs. 3 Legend: CI = confidence interval; CPC = Cerebral Performance Categories Scale; OR = odds ratio; ROSC = return of spontaneous circulation; SHA = survival to hospital admission; SHD = survival to hospital discharge. Note: Not all outcomes were reported in every study. "No. of studies" refers to the studies included in the analysis for the particular outcome.

The time of arrival of EMS teams on site was longer during the COVID-19 period. This parameter is a critical predictor of resuscitation success, as every minute of delay significantly reduces the survival chances [48, 54] . Our findings are consistent with those reported by Yu [53] , who showed that not only were response times longer since COVID-19 began but that the rapid deployment of advanced lifesaving procedures was crucial to patient survival. This was noted in Italy and Spain as well, where EMS response time was prolonged. However, in these environments, the authors emphasize that an increased Legend: CI = confidence interval; CPC = Cerebral Performance Categories Scale; OR = odds ratio; ROSC = return of spontaneous circulation; SHA = survival to hospital admission; SHD = survival to hospital discharge. Note: Not all outcomes were reported in every study. "No. of studies" refers to the studies included in the analysis for the particular outcome.

The time of arrival of EMS teams on site was longer during the COVID-19 period. This parameter is a critical predictor of resuscitation success, as every minute of delay significantly reduces the survival chances [48, 54] . Our findings are consistent with those reported by Yu [53] , who showed that not only were response times longer since COVID-19 began but that the rapid deployment of advanced lifesaving procedures was crucial to patient survival. This was noted in Italy and Spain as well, where EMS response time was prolonged. However, in these environments, the authors emphasize that an increased 

The time of arrival of EMS teams on site was longer during the COVID-19 period. This parameter is a critical predictor of resuscitation success, as every minute of delay significantly reduces the survival chances [48, 54] . Our findings are consistent with those reported by Yu [53] , who showed that not only were response times longer since COVID-19 began but that the rapid deployment of advanced lifesaving procedures was crucial to patient survival. This was noted in Italy and Spain as well, where EMS response time was prolonged. However, in these environments, the authors emphasize that an increased volume of calls may have been the cause of these delays [47] , as was the case in Detroit [45] . Because the initial response is vital to increasing the chance of a good outcome in OHCA patients [55] , a public health initiative to encourage people to perform CPR [56] may improve survival [24] . Interestingly, a study from Osaka Japan found that although the bystander CPR, as well as AED usage, was lower during the COVID period, the outcomes measured by the 1-month survival with favorable neurological outcomes did not change [46] .

We found a significant difference in shockable rhythms between pre-COVID-19 and COVID-19 patients; shockable rhythm is less frequent during the COVID-19 pandemic. This finding is worrisome, as the shockable rhythms have a more favorable prognosis [57] . Because of the risk of contracting SARS-CoV-2, some authors have suggested that, in patients >60 years old with nonshockable rhythms, resuscitation should be terminated early due to the high risk of contamination of the EMS team [58] . Additionally, Baldi et al. reported the decrease in bystander CPR and subsequent decline in EMS provided resuscitation over the analyzed periods of 2019 and 2020 [26] .

Interestingly we found that the use of advanced airway management techniques was more prevalent since COVID-19, both in the form of endotracheal intubation, as well as supraglottic airway devices. This finding is particularly interesting, as initial guidelines placed high value on the avoidance of airway manipulation to avoid aerosol formation [59] , which increases the risk of SARS-CoV-2 transmission [60] . However, more recent data show that although intubation generates aerosols, it poses a low risk of infection when performed by an experienced healthcare provider following proper protocols [61, 62] . Additionally, simulation studies show that intubation is a safe procedure, provided that the healthcare professional is wearing PPE. However, to complicate the analysis, the wearing of PPE during the procedure may itself result in prolonged time to resuscitation [63] [64] [65] .

When analyzing time to ROSC, we found that it was longer before COVID-19. Semeraro [50] confirmed this finding in his data analysis as well. The reason behind these results may lie in the coexisting respiratory arrest [66] . Other studies also report lowering of the time to ROSC since COVID-19 [29, 44] due to this phenomenon. Interestingly when analyzing the Detroit population, Shinobi found no difference in ROSC between COVID and pre-COVID-19 periods [41] .

In the analyzed population, the survival to hospital admission with spontaneous circulation was significantly higher before COVID-19. However, we must note that over the course of COVID-19, many patients did not receive advanced life support (ALS), therefore further reducing their survival chances [67, 68] . The analysis by Sultanian et al. [51] showed more than a threefold increase in 30-day mortality among COVID-19-positive patients. Additionally, during the initial phase of the COVID-19 pandemic, many patients may have been afraid to seek help despite coronary symptoms, which could have prolonged the treatment and diagnostic process, thus resulting in worse outcomes [69] .

Both survival to overall hospital discharge and survival to hospital discharge with CPC 1-2 were higher in the pre-pandemic period. The neurological damage resulting from cardiac arrest [70] is further exacerbated by the COVID-19 infection [71] . These findings are in line with those achieved by Glober et al. [33] , who also underlined that patients were more likely to die in the field, with those who survive having a worse neurological status. The data provided by Ahn further reinforce these conclusions [23] . In the patient group analyzed by Cho, not a single patient who was diagnosed with COVID achieved a favorable neurological outcome [30] .

In the COVID-19 era, the prognosis of OHCA is worse. Moreover, cardiac arrests occurred more frequently at home, and bystanders used AED less frequently.

Supplementary Materials: The following are available online at https://www.mdpi.com/article/ 10.3390/jcm10235573/s1, Table S1 : Characteristics of included studies, Table S2 : Methodology characteristics of included trials, Table S3 : PRISMA checklist, Figure S1 : A summary table of review authors' judgments for each risk of bias item for each study, Figure S2 : A plot of the distribution of review authors' judgments across studies for each risk of bias item, Figure S3 : Funnel plot to illustrate possible publication bias due to time to Emergency Medical Service arrival, Figure S4 : Funnel plot to illustrate possible publication bias due to occurrence of shockable rhythm, Figure S5 : Funnel plot to illustrate possible publication bias due to survival to hospital admission, Figure S6 : Funnel plot to illustrate possible publication bias due to survival to hospital discharge. 

Out-of-hospital cardiac arrest during the Covid-19 outbreak in Italy

The impact of COVID-19 on airway management in prehospital resuscitation

COVID-19 Lombardy ICU Network. Risk Factors Associated with Mortality Among Patients With COVID-19 in Intensive Care Units in

Resuscitation teamwork during the COVID-19 pandemic in the emergency department: Challenges and solutions

Mechanical chest compression devices as an option for out-of-hospital cardiac arrest in COVID-19 pandemic

Vilacosta, I. Cardiovascular comorbidity and death from COVID-19: Prevalence and differential characteristics

COVID-19 challenge for modern medicine

Cardiopulmonary Resuscitation during the COVID-19 pandemic. Do supraglottic airways protect against aerosol-generation? Resuscitation

Ethics of Codes and Codes of Ethics: When Is It Ethical to Provide Cardiopulmonary Resuscitation During the COVID-19 Pandemic?

Outcomes of Cardiopulmonary Resuscitation in Patients With COVID-19-Limited Data, but Further Reason for Action

Impact of the presence of heart disease, cardiovascular medications and cardiac events on outcome in COVID-19

Out-of-hospital cardiac arrest treated by emergency medical service teams during COVID-19 pandemic: A retrospective cohort study

European Resuscitation Council COVID-Guideline Writing Groups. European Resuscitation Council COVID-19 guidelines executive summary

Impact of Coronavirus Disease 2019 on Out-of-Hospital Cardiac Arrest Survival Rate: A Systematic Review with Meta-Analysis

The PRISMA 2020 statement: An updated guideline for reporting systematic reviews

Estimating the mean and variance from the median, range, and the size of a sample

Cochrane Handbook for Systematic Reviews of Interventions Version

ROBINS-I: A tool for assessing risk of bias in non-randomized studies of interventions

Risk-of-bias VISualization (robvis): An R package and Shiny web app for visualizing risk-of-bias assessments

The interpretation of random-effects meta-analysis in decision models

Bias in meta-analysis detected by a simple, graphical test

Operating characteristics of a rank correlation test for publication bias

Impact of the COVID-19 outbreak on adult out-of-hospital cardiac arrest outcomes in Daegu, South Korea: An observational study

Assessment of changes in cardiopulmonary resuscitation practices and outcomes on 1005 victims of out-of-hospital cardiac arrest during the COVID-19 outbreak: Registry-based study

Coronavirus Disease 2019 and Out-of-Hospital Cardiac Arrest: No Survivors

Treatment of out-of-hospital cardiac arrest in the COVID-19 era: A 100 days experience from the Lombardy region

Out-of-hospital cardiac arrests and mortality in Swiss Cantons with high and low COVID-19 incidence: A nationwide analysis

Collateral damage: Hidden impact of the COVID-19 pandemic on the out-of-hospital cardiac arrest system-of-care

Outcomes for Out-of-Hospital Cardiac Arrest in the United States During the Coronavirus Disease

WinCOVID-19 consortium. Preparedness of personal protective equipment and implementation of new CPR strategies for patients with out-of-hospital cardiac arrest in the COVID-19 era

Indirect effects of COVID-19 on OHCA in a low prevalence region

Out-of-Hospital Cardiac Arrest in London during the COVID-19 pandemic

Out-of-hospital cardiac arrest volumes and characteristics during the COVID-19 pandemic

Use of out-of-hospital cardiac arrest registries to assess COVID-19 home mortality

Evaluation of a revised resuscitation protocol for out-of-hospital cardiac arrest patients due to COVID-19 safety protocols: A single-center retrospective study in Japan

WinCOVID-19 consortium. Confirmation of COVID-19 in Out-of-Hospital Cardiac Arrest Patients and Postmortem Management in the Emergency Department during the COVID-19 Outbreak

Characteristics Associated With Out-of-Hospital Cardiac Arrests and Resuscitations During the Novel Coronavirus Disease

Impact of COVID-19 on Out-of-Hospital Cardiac Arrest in Singapore

The Comparison of Emergency Medical Service Responses to and Outcomes of Out-of-hospital Cardiac Arrest before and during the COVID-19 Pandemic in an Area of

Out-of-hospital cardiac arrest during the COVID-19 pandemic

Effects of the COVID-19 pandemic on out-of-hospital cardiac arrest care in Detroit

Impact of Different Waves of COVID-19 on Emergency Medical Services and Out-of-Hospital Cardiopulmonary Arrest in Madrid, Spain

Caseload and cardiopulmonary arrest management by an out-of-hospital emergency service during the COVID-19 pandemic

Impact of COVID-19 'circuit-breaker' measures on emergency medical services utilisation and out-of-hospital cardiac arrest outcomes in Singapore

Comparison of Out-of-Hospital Cardiac Arrests and Fatalities in the Metro Detroit Area During the COVID-19 Pandemic With Previous-Year Events

Influence of COVID-19 pandemic on bystander interventions, emergency medical service activities, and patient outcomes in out-of-hospital cardiac arrest in Osaka City

Influence of the Covid-19 pandemic on out-of-hospital cardiac arrest. A Spanish nationwide prospective cohort study

Out-of-hospital cardiac arrest during the COVID-19 pandemic in the Province of Padua

Impact of Coronavirus Disease 2019 Pandemic on the Incidence and Management of Out-of-Hospital Cardiac Arrest in Patients Presenting With Acute Myocardial Infarction in England

Out-of-hospital cardiac arrest during the COVID-19 era in Bologna: System response to preserve performances

Cardiac arrest in COVID-19: Characteristics and outcomes of in-and out-of-hospital cardiac arrest. A report from the Swedish Registry for Cardiopulmonary Resuscitation

Out-of-Hospital Cardiac Arrest Response and Outcomes During the COVID-19 Pandemic

Impact of the COVID-19 pandemic on emergency medical service response to out-of-hospital cardiac arrests in Taiwan: A retrospective observational study

The relationship between time to arrival of emergency medical services (EMS) and survival from out-of-hospital ventricular fibrillation cardiac arrest

Outcomes of patients 65 years or older after out-of-hospital cardiac arrest based on the location of cardiac arrest in Japan

Impact of bystander-focused public health interventions on cardiopulmonary resuscitation and survival: A cohort study

Comparing the prognosis of those with initial shockable and non-shockable rhythms with increasing durations of CPR: Informing minimum duration of resuscitation

Should we resuscitate COVID-19 patients with nonshockable rhythms?

Recommendations for Endotracheal Intubation of COVID-19 Patients

Turbulent Gas Clouds and Respiratory Pathogen Emissions: Potential Implications for Reducing Transmission of COVID-19

A quantitative evaluation of aerosol generation during tracheal intubation and extubation

Clinical Aerosolisation Study Group. Aerosolisation during tracheal intubation and extubation in an operating theatre setting

Endotracheal intubation of COVID-19 patients by paramedics using a box barrier: A randomized crossover manikin study

Resuscitation of the patient with suspected/confirmed COVID-19 when wearing personal protective equipment: A randomized multicenter crossover simulation trial

Comparison of different chest compression positions for use while wearing CBRN-PPE: A randomized crossover simulation trial

Effects of COVID-19 pandemic on out-of-hospital cardiac arrests: A systematic review

Impact of COVID-19 on bystander cardiopulmonary resuscitation in out-of-hospital cardiac arrest: Is it as bad as we think?

Resuscitation in COVID-19 patients: What do we know and what should we do?

The covid-19 pandemic and the incidence of acute myocardial infarction

Neurologic prognosis in cardiac arrest patients treated with therapeutic hypothermia

Neurological Manifestations of COVID-19 (SARS-CoV-2): A Review

Acknowledgments: Not applicable.

The authors declare no conflict of interest.