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Adult Intensive Care Services and Critical Care Research Group, The Prince Charles Hospital, Brisbane, Queensland, AustraliaUniversity of Queensland, Brisbane, Queensland University of Technology Brisbane and Bond University, Gold Coast, Queensland, Australia
Department of Intensive Care Medicine, Peninsula Health, Frankston, Victoria, AustraliaFaculty of Medicine, Nursing and Health Sciences, Monash University, Clayton, Victoria, Australia
The impact of COVID-19 on pre-hospital and hospital services and hence on the prevalence and outcomes of out-of-hospital cardiac arrests (OHCA) remain unclear. The review aimed to evaluate the influence of the COVID-19 pandemic on the incidence, process, and outcomes of OHCA.
Methods
A systematic review of PubMed, EMBASE, and pre-print websites was performed. Studies reporting comparative data on OHCA within the same jurisdiction, before and during the COVID-19 pandemic were included. Study quality was assessed based on the Newcastle-Ottawa Scale.
Results
Ten studies reporting data from 35,379 OHCA events were included. There was a 120% increase in OHCA events since the pandemic. Time from OHCA to ambulance arrival was longer during the pandemic (p = 0.036). While mortality (OR = 0.67, 95%-CI 0.49−0.91) and supraglottic airway use (OR = 0.36, 95%-CI 0.27−0.46) was higher during the pandemic, automated external defibrillator use (OR = 1.78 95%-CI 1.06–2.98), return of spontaneous circulation (OR = 1.63, 95%CI 1.18-2.26) and intubation (OR = 1.87, 95%-CI 1.12-–3.13) was more common before the pandemic. More patients survived to hospital admission (OR = 1.75, 95%-CI 1.42–2.17) and discharge (OR = 1.65, 95%-CI 1.28–2.12) before the pandemic. Bystander CPR (OR = 1.18, 95%-CI 0.95-1.46), unwitnessed OHCA (OR = 0.84, 95%-CI 0.66–1.07), paramedic-resuscitation attempts (OR = 1.19 95%-CI 1.00–1.42) and mechanical CPR device use (OR = 1.57 95%-CI 0.55–4.55) did not defer significantly.
Conclusions
The incidence and mortality following OHCA was higher during the COVID-19 pandemic. There were significant variations in resuscitation practices during the pandemic. Research to define optimal processes of pre-hospital care during a pandemic is urgently required.
The novel coronavirus disease 2019 (COVID-19) pandemic, caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has been associated with more than 39 million cases and 1 million deaths worldwide as of October 16th 2020.
Health systems are under significant sustained stress with many parts of world experiencing second and subsequent waves of infection. The understanding of how the pandemic affects overall population health and access to health care; the nature and extent of disruptions it causes to pre-hospital and in hospital health care delivery is still evolving.
For example, an increase in out-of-hospital cardiac arrest (OHCA) incidence has been reported since the very early phase of the COVID-19 epidemic.
A recent population-based cross-sectional study reported that out-of-hospital cardiac arrests had increased 3-fold during the 2020 COVID-19 period when compared with during the comparison period in 2019.
Characteristics associated with out-of-hospital cardiac arrests and resuscitations during the novel coronavirus disease 2019 pandemic in New York City.
Patients with OHCA during 2020 were older, more likely to have comorbidities and substantially less likely to have return and sustained return of spontaneous circulation.
Characteristics associated with out-of-hospital cardiac arrests and resuscitations during the novel coronavirus disease 2019 pandemic in New York City.
The chain of survival refers to a series of actions such as early access, early cardiopulmonary resuscitation (CPR), early defibrillation, early advanced life support and early post resuscitative care. These actions should be optimally executed to reduce the mortality associated with OHCA. Like any chain, the chain of survival is only as strong as its weakest link.
A pandemic can disrupt this chain of survival in multiple ways and influence patient outcomes.
The study hypothesis was that the incidence of OHCA and the associated mortality was higher during the COVID-19 pandemic period when compared to an earlier period. In this systematic review and meta-analysis, the authors aimed to determine the influence of the COVID-19 pandemic on the incidence, processes of care and mortality among OHCA patients.
Methods
This systematic review and meta-analysis were reported using the PRISMA framework
Studies reporting comparative OHCA data before and during the COVID-19 pandemic within the same location were included. Studies were excluded if (a) results of original research were not presented; (b) the study only reported on deceased patients.
Search strategy, information sources and study selection
Two authors independently searched the publicly available COVID-19 living systematic review.
This living systematic review provides a dynamic update of research papers related to COVID-19 that are indexed by PubMed, EMBASE, MedRxiv and BioRxiv, and has been validated in previously published COVID-19-related research.
Data was extracted between 01/01/2020 to 16/10/2020 using the search terms “arrest”, “OHCA”, “OOHCA” within the title and the abstract columns of the systematic review list. These terms were combined with the Boolean operator “OR”. Pre-print and non-English language articles were considered. Conflicts in data extraction were resolved by discussion between the reviewers or adjudication by a third author.
Quality assessment and risk of bias in individual studies
The Newcastle-Ottawa Scale (NOS) is a quality assessment tool used to evaluate non-randomized studies based on an eight-item score divided into three domains.
GA Wells BS, D O’Connell, J Peterson, V Welch, M Losos, P Tugwell. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses.
These domains assess selection, comparability, and ascertainment of the outcome of interest. NOS was used by the two reviewers to independently evaluate the quality of included studies and assess for risk of bias. The same set of decision rules was used by each reviewer to score the studies. Any discrepancies from the NOS were reviewed and resolved by a third author.
Data analysis and data collection process
To evaluate the effect of the COVID-19 pandemic, the studies with direct comparison to an earlier time frame (termed “before pandemic”) were selected. This enabled a direct comparison between the two-time frames to help understand any differences in incidences.
Statistical analyses were performed using the Review Manager 5.4 (Cochrane Collaboration) and Stata/MP 15.1 (Statacorp). Numerical data was summarized using mean and standard deviation and categorical data using proportion and percentage. To enable an analysis of results between studies, median values were converted to means, derived using an estimation formula.
Between-group differences were compared using Fischer’s exact test. An analysis of non-parametric values was conducted using the Kruskal Wallace test. A p-value <0.05 was considered statistically significant. The Mentel-Haenszel random-effects model demonstrate better properties in the presence of heterogeneity accounting for both within-study and between-study variances which was considered for the pooled odds ratio (OR). Results were presented in Forest plots. Heterogeneity was tested by using the χ² test on Cochran’s Q statistic, which was calculated by means of H and I² indices. The I² index estimates the percentage of total variation across studies based on true between-study variances rather than on chance. Conventionally, I2 values of 0–25% indicate low heterogeneity, 26–75% indicate moderate heterogeneity, and 76–100% indicate substantial heterogeneity.
Corresponding authors were contacted for additional information, where data were incomplete. Study period and location were analyzed as part of the data collection process, and studies were excluded if a significant overlap in patient cohorts were identified.
Study outcomes
The primary outcome was to evaluate the incidence and mortality rate of OHCA during the COVID-19 pandemic.
Additional secondary outcomes include analyzing the characteristics and outcomes of OHCA during the COVID-19 pandemic. Time from OHCA notification to ambulance arrival was also analyzed. The frequency of COVID-19 patients among OHCA was also assessed.
Results
A total of 209 studies were obtained from the living systematic review, with 23 full-text articles assessed for eligibility. Ten studies across five countries (Australia, France, Italy, Spain and USA) were included in the qualitative and statistical analysis.
Characteristics associated with out-of-hospital cardiac arrests and resuscitations during the novel coronavirus disease 2019 pandemic in New York City.
Rosell Ortiz F., Fernández del Valle P., Knox E.C., Jiménez Fábrega X., Navalpotro Pascual J.M., Mateo Rodríguez I., et al. Influence of the Covid-19 pandemic on out-of-hospital cardiac arrest. A Spanish nationwide prospective cohort study. Resuscitation.
Characteristics associated with out-of-hospital cardiac arrests and resuscitations during the novel coronavirus disease 2019 pandemic in New York City.
Rosell Ortiz F., Fernández del Valle P., Knox E.C., Jiménez Fábrega X., Navalpotro Pascual J.M., Mateo Rodríguez I., et al. Influence of the Covid-19 pandemic on out-of-hospital cardiac arrest. A Spanish nationwide prospective cohort study. Resuscitation.
Characteristics associated with out-of-hospital cardiac arrests and resuscitations during the novel coronavirus disease 2019 pandemic in New York City.
Rosell Ortiz F., Fernández del Valle P., Knox E.C., Jiménez Fábrega X., Navalpotro Pascual J.M., Mateo Rodríguez I., et al. Influence of the Covid-19 pandemic on out-of-hospital cardiac arrest. A Spanish nationwide prospective cohort study. Resuscitation.
The mean age reported among nine studies was 70.8 years during the COVID-19 pandemic, and 65.6 years before the pandemic. Time from call to ambulance arrival was significantly higher during the pandemic (p = 0.036). The incidence and outcomes of OHCA of each study is outlined in Table 1.
Table 1Summary of studies.
Lai 2020
Baldi 2020
Ball 2020
Elmer 2020
Marijon 2020
Ortiz 2020
Paoli 2020
Sayre 2020
Semeraro 2020
Uy-Evanado 2020
Total
p-value
Location of study
New York, USA
Lombardy, Italy
Victoria, Australia
Pennsylvania, USA
Paris, France
Spain
Pauda, Italy
Washington, USA
Bologna, Italy
Oregon and California, USA
NOS Score
Good
Fair
Good
Fair
Fair
Good
Fair
Fair
Fair
Good
Time period
Before pandemic
March 1 to April 25, 2019
February 21 to April 21, 2019
March 16 to May 12, 2017−2019
January 2016 to February 2020
March 18 to April 28, 2019
April 1−30 2017, and February 1 to March 31 2018
March 1 to April 30, 2019
January 1 to February 25, 2019
January 1 to June 30, 2019
March 1 to May 31, 2019
During pandemic
March 1 to April 25, 2019
February 21 to April 20, 2020
March 16 to May 12, 2020
March 1 to May 25, 2020
March 16 to April 26, 2020
March 11 to April 30, 2020
March 1 to April 30, 2020
February 26 to April 15, 2020
January 1 to June 30, 2020
March 1 to May 31, 2020
Sample Size
Before pandemic
2302
321
2599
12252
3052^
1723#
206
540
563
231
23789
NA
During pandemic
6709
490
935
683
521
683#
200
527
624
278
11590
NA
Difference in OHCA incidence
2019
2302
321
NR*
NR*
395
NR*
206
NR*
563
231
4018
NA
2020
6709
490
NR*
NR*
521
NR*
200
NR*
624
278
8822
Percentage change
191.4%
52.6%
NR*
NR*
31.9%
NR*
−3%
NR*
10.8%
20.3%
119.6%
Age (Years), Mean (SD)
Before pandemic
68 (19)
77 (14)
66 (19)
63 (19)
69 (18)
66 (17)
77 (14)
NR
83 (13)
69 (17)
65.6
NA
During pandemic
72 (18)
76 (13)
68 (19)
64 (19)
70 (17)
64 (16)
79 (17)
NR
83 (13)
65 (18)
70.8
NA
Male patients, N (%)
Before pandemic
752/1336 (56.3%)
188/321 (58.6%)
845/1218# (69.4%)
7700/12252 (62.8%)
1826/3047 (59.9%)
1210/1723# (70.2%)
98/179 (54.7%)
NR
284/563 (50.4%)
137/231 (59.3%)
13040/20870 (62.5%)
<0.001
During pandemic
2183/3989 (54.7%)
321/490 (65.5%)
250/380# (65.8%)
430/683 (63.0%)
334/519 (64.4%)
433/623# (69.5%)
89/175 (50.9%)
NR
318/624 (51.0%)
174/278 (62.6%)
4532/7761 (58.4%)
Mortality, N (%)
Before pandemic
1922/2302 (83.5%)
156/321 (48.6%)
827/1218# (67.9%)
6302/12252 (51.4%)
2357/3052 (77.2%)
1109/1634# (67.9%)
200/206 (97.1%)
292/540 (54.1%)
509/563 (90.4%)
157/231 (68.0%)
13831/22319 (62.0%)
<0.001
During pandemic
6244/6709 (93.1%)
253/490 (51.6%)
285/380# (75.0%)
329/683 (48.2%)
454/521 (87.1%)
473/580# (81.6%)
194/200 (97.0%)
297/527 (56.4%)
586/624 (93.9%)
213/278 (76.6%)
9328/10992 (84.9%)
Bystander CPR, N (%)
Before pandemic
441/1336 (33.0%)
87/192 (45.3%)
889/1218# (73.0%)
4125/12,252 (33.7%)
1165/1822 (63.9%)
788/1723# (45.7%)
15/60 (25.0%)
227/540 (42.0%)
29/110# (26.4%)
142/231 (61.5%)
7908/19484 (40.6%)
0.003
During pandemic
1359/3989 (34.1%)
89/257 (34.6%)
299/380# (78.7%)
246/683 (36.0%)
239/500 (47.8%)
230/623# (36.9%)
10/55 (18.2%)
207/527 (39.3%)
30/95# (31.6%)
141/278 (50.7%)
2850/7387 (38.6%)
Unwitnessed OHCA, N (%)
Before pandemic
982/1336 (73.5%)
147/321 (45.8%)
329/1218# (27.0%)
8772/12252 (71.6%)
1021/2908 (35.1%)
392/1723# (22.8%)
42/59 (71.1%)
NR
NR
109/231 (47.2%)
11794/20048 (58.8%)
<0.001
During pandemic
2909/3989 (72.9%)
261/490 (53.3%)
179/380# (47.1%)
466/683 (68.2%)
206/500 (41.2%)
130/623# (20.9%)
39/52 (75.0%)
NR
NR
138/278 (49.6%)
4328/6995 (61.9%)
EMS Resuscitation attempted, N (%)
Before pandemic
1336/2302 (58.0%)
222/321 (69.2%)
1218/2599 (46.9%)
NR
NR
NR
48/90 (53.3%)
248/540 (45.9%)
110/563 (19.5%)
NR
3182/6415 (49.6%)
<0.001
During pandemic
3989/6709 (59.5%)
324/490 (64.1%)
380/935 (40.6%)
NR
NR
NR
45/114 (39.5%)
230/527 (43.6%)
95/624 (15.2%)
NR
5053/9399 (53.8%)
ROSC, N (%)
Before pandemic
463/1336 (34.7%)
44/222 (19.8%)
416/1218 (34.2%)
1529/12252 (12.5%)
NR
525/1723# (30.5%)
4/206 (1.9%)
NR
54/563 (9.6%)
95/231 (41.1%)
3130/17751 (17.6%)
0.22
During pandemic
727/3989 (18.2%)
27/314 (8.6%)
112/380 (29.5%)
95/683 (13.9%)
NR
107/623# (17.2%)
2/200 (1.0%)
NR
38/624 (6.1%)
95/278 (34.2%)
1203/7091 (17.0%)
Shockable cardiac rhythm/shocked events, N (%)
Before pandemic
38/345 (11.0%)
37/222 (16.7%)
318/1218# (26.1%)
NR
472/2471 (19.1%)
386/1723# (22.4%)
NR
NR
34/563 (6.0%)
64/231 (27.7%)
1349/6773 (19.9%)
<0.001
During pandemic
45/1254 (3.6%)
36/314 (11.5%)
90/380# (23.7%)
NR
46/500 (9.2%)
118/623# (18.9%)
NR
NR
33/624 (5.3%)
64/278 (23.0%)
432/3973 (10.9%)
OHCA at home, N (%)
Before pandemic
NR
267/321 (83.2%)
965/1218# (79.2%)
NR
2336/3042 (76.8%)
1042/1723# (60.5%)
NR
NR
82/110# (74.5%)
145/231 (62.8%)
4837/6645 (72.8%)
<0.001
During pandemic
NR
442/490 (90.2%)
342/380# (90.0%)
NR
460/510 (90.2%)
478/623# (76.7%)
NR
NR
65/95# (68.4%)
210/278 (75.5%)
1997/2376 (84.0%)
Intubation
Before pandemic
NR
NR
594/1218# (48.8%)
2760/6571 (42.0%)
NR
1224/1723# (71.0%)
NR
NR
NR
NR
5589/10848 (51.5%)
<0.001
During pandemic
NR
NR
171/380# (45.0%)
127/353 (36.0%)
NR
320/630# (50.8%)
NR
NR
NR
NR
2533/5352 (47.3%)
Supraglottic airway
Before pandemic
NR
NR
NR
904/6571 (13.8%)
NR
103/1723# (6.0%)
NR
NR
NR
NR
1200/9630 (12.5%)
<0.001
During pandemic
NR
NR
NR
89/353 (25.2%)
NR
110/630# (17.5%)
NR
NR
NR
NR
1584/4972 (31.9%)
Mechanical CPR
Before pandemic
NR
23/138 (16.7%)
177/1218# (14.5%)
NR
NR
NR
NR
NR
NR
NR
200/1356 (14.7%)
0.24
During pandemic
NR
9/138 (6.5%)
56/380# (14.7%)
NR
NR
NR
NR
NR
NR
NR
65/518 (12.5%)
AED use
Before pandemic
NR
NR
84/1218# (6.9%)
1744/12252 (14.2%)
33/1092 (3.0%)
173/1723# (10.0%)
NR
NR
NR
12/231 (5.2%)
2046/16516 (12.4%)
<0.001
During pandemic
NR
NR
15/380# (3.9%)
104/683 (15.2%)
2/500 (0.4%)
43/630# (6.8%)
NR
NR
NR
4/278 (1.4%)
168/2471 (6.8%)
Survival to hospital admission
Before pandemic
NR
44/222 (19.8%)
359/1218# (29.5%)
NR
695/3052 (22.8%)
525/1634# (32.1%)
NR
NR
42/110# (38.2%)
74/231 (32.0%)
1739/6467 (26.9%)
<0.001
During pandemic
NR
27/314 (8.6%)
92/380# (24.2%)
NR
67/521 (12.9%)
107/580# (18.4%)
NR
NR
31/95# (32.6%)
65/278 (23.4%)
389/2168 (17.9%)
Survival to hospital discharge
Before pandemic
NR
21/222 (9.5%)
142/1218# (11.7%)
NR
164/3052 (5.4%)
168/1723# (9.8%)
NR
NR
22/110# (20.0%)
34/231 (14.7%)
551/6556 (8.4%)
0.002
During pandemic
NR
16/314 (5.1%)
22/380# (5.8%)
NR
16/517 (3.1%)
42/623# (6.7%)
NR
NR
23/95# (24.2%)
22/278 (7.9%)
141/2207 (6.4%)
Call to arrival in minutes, Median (IQR)
Before pandemic
5.1 (2.3−7.2)
12 (9−15)
8.5 (6.6−11.4)
NR
9.4 (7.9−12.6)
12 (8−19)
15 (11−19)
NR
9 (7−13)
6.4 (1.6−13.7)
NA
0.036
During pandemic
5.9 (2.3−9.6)
15 (11−20)
9.8 (8.0−12.8)
NR
10.4 (8.4−13.8)
15 (9−23)
16 (12−22)
NR
9 (7−12)
7 (0.7−22.8)
NA
Etiology of OHCA, N (%)
Medical
Before pandemic
NR
175/204 (58.8%)
979/1218# (80.4%)
11,153/12252 (91.0%)
NR
NR
287/321 (89.4%)
NR
99/110# (90.0%)
NR
12693/14105 (90.0%)
0.56
During pandemic
NR
179/197 (90.9%)
293/380# (77.1%)
643/683 (94.1%)
NR
NR
465/490 (94.9%)
NR
89/95# (93.7%)
NR
1669/1845 (90.5%)
Trauma
Before pandemic
43/2302 (1.9%)
17/204 (8.3%)
60/1218# (4.9%)
1099/12252 (9.0%)
NR
NR
28/321 (8.7%)
NR
6/110# (5.5%)
NR
1253/14105 (8.9%)
0.031
During pandemic
42/6709 (0.6%)
15/197 (7.6%)
22/380# (5.8%)
40/683 (5.9%)
NR
NR
13/490 (2.7%)
NR
4/95# (4.2%)
NR
136/1845 (7.4%)
Drowning
Before pandemic
NR
0/204 (0.0%)
NR
NR
NR
NR
0/321 (0.0%)
NR
1/110# (0.9%)
NR
1/635 (0.2%)
1.00
During pandemic
NR
1/197 (0.5%)
NR
NR
NR
NR
0/490 (0.0%)
NR
0/95# (0.0%)
NR
1/782 (0.1%)
Overdose
Before pandemic
NR
1/204 (0.5%)
58/1218# (4.8%)
NR
NR
NR
1/321 (0.3%)
NR
4/110# (3.6%)
NR
64/1853 (3.5%)
0.58
During pandemic
NR
0/197 (0.0%)
18/380# (4.7%)
NR
NR
NR
1/490 (0.2%)
NR
2/95# (2.1%)
NR
21/1162 (1.8%)
Asphyxia
Before pandemic
NR
7/204 (3.4%)
44/1218# (3.6%)
NR
NR
NR
5/321 (1.6%)
NR
NR
NR
56/1743 (3.2%)
1.00
During pandemic
NR
6/197 (3.0%)
15/380# (3.9%)
NR
NR
NR
11/490 (2.2%)
NR
NR
NR
32/1067 (3.0%)
NOS: Newcastle Ottawa Scale; USA: United States of America; SD: Standard deviation; N: Number; CPR: NR: Not reported; Cardiopulmonary resuscitation; OHCA: Out of hospital cardiac arrest; EMS: Emergency medical services; ROSC: Return of spontaneous circulation; AED: Automatic external defibrillator.
* The study did not compare the incidence of OHCA between 2019 and 2020 and was thus excluded from this analysis.
# Out of resuscitations attempted by emergency medical services.
^ Marijon et al looked at two different timeframes and compared the incidence and outcomes of OHCA against data from the pandemic period in 2020.
Table 2 summarizes the comparison of suspected and confirmed COVID-19 patients among the OHCA in 2020. Five studies (n = 2044) reported on the prevalence of COVID-19 infections among OHCA.
Primary outcome: incidence and mortality rate of OHCA during the COVID-19 pandemic
Six studies made a direct comparison of OHCA incidence between the same time period in 2020 and 2019 and recorded 8822 OHCA events in 2020 during the COVID-19 pandemic in contrast to 4018 OHCA in 2019, representing a 119.6% increase (Table 1).
Characteristics associated with out-of-hospital cardiac arrests and resuscitations during the novel coronavirus disease 2019 pandemic in New York City.
During the pandemic, all ten studies recorded 11,590 OHCA events. Outcomes were known for 10992 patients (94.8%), of which 9328 (84.9%) patients died. In comparison, the before pandemic group recorded 22319 OHCA across various comparison time periods with 13,831 (62.0%) deaths (p < 0.001). The forest plot for mortality of OHCA is illustrated in Fig. 2 (OR = 0.67, 95% CI 0.49−0.91; p = 0.01). Heterogeneity was high (I2 = 93%).
Fig. 2Forest plot comparison before COVID-19 pandemic vs. during COVID-19 pandemic for mortality.
The incidence proportion of OHCA due to a medical cause was similar before and during the pandemic (90.0% (12693/14105) versus 90.5% (1669/1845), p = 0.56; OR = 0.69, 95% CI 0.45-1.06;0.45–1.06; p = 0.09; I2 = 75%).
Characteristics associated with out-of-hospital cardiac arrests and resuscitations during the novel coronavirus disease 2019 pandemic in New York City.
However, trauma-related OHCA was more common before the pandemic (8.9% (1253/14105) versus 7.4% (136/1845), p = 0.031; OR = 1.69, 95% CI 1.07–2.69; p = 0.03; I2 = 76%).
Characteristics associated with out-of-hospital cardiac arrests and resuscitations during the novel coronavirus disease 2019 pandemic in New York City.
Bystander CPR (Fig. 3b) was reported in all ten studies in a total of 7908/19549 patients (40.5%) before pandemic and 2850/7322 patients (38.9%) during the pandemic (p < 0.001).
Characteristics associated with out-of-hospital cardiac arrests and resuscitations during the novel coronavirus disease 2019 pandemic in New York City.
Bystander CPR occurred more frequently before the pandemic but was not statistically significant (OR = 1.08 95% CI 0.86–1.35; p = 0.51; I2 = 88%).
Unwitnessed OHCA (Fig. 3c) was reported in eight studies across 11794/20048 patients (58.8%) before the pandemic and 4328/6995 patients (61.9%) during the pandemic (p < 0.001).
Characteristics associated with out-of-hospital cardiac arrests and resuscitations during the novel coronavirus disease 2019 pandemic in New York City.
Rosell Ortiz F., Fernández del Valle P., Knox E.C., Jiménez Fábrega X., Navalpotro Pascual J.M., Mateo Rodríguez I., et al. Influence of the Covid-19 pandemic on out-of-hospital cardiac arrest. A Spanish nationwide prospective cohort study. Resuscitation.
Unwitnessed OHCA occurred less often before the pandemic, however, was not statistically significant (OR = 0.84 95% CI 0.66–1.07; p = 0.17; I2 = 89%).
Resuscitation was attempted by paramedics in six studies in a total of 3182/6415 patients (49.6%) before the pandemic and 5053/9399 patients (53.8%) during the pandemic (p < 0.001).
Characteristics associated with out-of-hospital cardiac arrests and resuscitations during the novel coronavirus disease 2019 pandemic in New York City.
While there was no difference in the number of arrests who had resuscitation attempted in the two timeframes (OR = 1.19 95% CI 1.00–1.42; p = 0.05; I2 = 73%), only one study reported an increase in frequency of resuscitation attempts during the pandemic (Fig. 3d).
Characteristics associated with out-of-hospital cardiac arrests and resuscitations during the novel coronavirus disease 2019 pandemic in New York City.
ROSC (Fig. 3e) was achieved in eight studies in a total of 3130/17751 patients (17.6%) before the pandemic and 1203/7091 patients (17.0%) during the pandemic (p = 0.22).
Characteristics associated with out-of-hospital cardiac arrests and resuscitations during the novel coronavirus disease 2019 pandemic in New York City.
Rosell Ortiz F., Fernández del Valle P., Knox E.C., Jiménez Fábrega X., Navalpotro Pascual J.M., Mateo Rodríguez I., et al. Influence of the Covid-19 pandemic on out-of-hospital cardiac arrest. A Spanish nationwide prospective cohort study. Resuscitation.
ROSC occurred more frequently before the pandemic (OR = 1.63 95% CI 1.18–2.26; p = 0.003; I2 = 90%).
OHCA (Fig. 3f) due to shockable rhythm or shocked events was reported in seven studies in a total of 1349/6773 patients (19.9%) before the pandemic and 432/3973 patients (10.9%) during the pandemic (p < 0.001).
Characteristics associated with out-of-hospital cardiac arrests and resuscitations during the novel coronavirus disease 2019 pandemic in New York City.
Shockable rhythm or shocked events occurred more frequently before the pandemic (OR = 1.57 95% CI 1.17–2.09; p = 0.002; I2 = 78%).
There were more OHCA occurring at home during the pandemic (Fig. 3g). Across six studies, 4837/6645 OHCA occurred at home before the pandemic (72.8%) compared to 1997/2376 arrests (84.0%) during the pandemic (p < 0.001).
Rosell Ortiz F., Fernández del Valle P., Knox E.C., Jiménez Fábrega X., Navalpotro Pascual J.M., Mateo Rodríguez I., et al. Influence of the Covid-19 pandemic on out-of-hospital cardiac arrest. A Spanish nationwide prospective cohort study. Resuscitation.
Characteristics associated with out-of-hospital cardiac arrests and resuscitations during the novel coronavirus disease 2019 pandemic in New York City.
Rosell Ortiz F., Fernández del Valle P., Knox E.C., Jiménez Fábrega X., Navalpotro Pascual J.M., Mateo Rodríguez I., et al. Influence of the Covid-19 pandemic on out-of-hospital cardiac arrest. A Spanish nationwide prospective cohort study. Resuscitation.
More patients were intubated before the pandemic (51.5% (5589/10848) versus 47.3% (2533/5352), p < 0.001; OR = 1.87, 95% CI 1.12–3.13; p = 0.02; I2 = 97%) (Fig. 3h). While supraglottic airway was less frequently used before the pandemic (12.5% (1200/9630) versus 31.9% (1584/4972), p < 0.001); OR = 0.36 95% CI 0.27−0.46; p < 0.0001; I2 = 75%) (Fig. 3i).
There was no difference in the use of mechanical CPR devices for OHCA before and during the pandemic, as reported in two studies (14.7% (200/1356) versus 12.5% (65/518); p = 0.24); and did not reach statistical significance (OR = 1.57 95% CI 0.55–4.55; p = 0.40; I2 = 83%) (Fig. 3j).
Automated external defibrillators (AEDs,) reported in five studies, were used more frequently before the pandemic (12.4% (2046/16516) versus 6.8% (168/2471), p < 0.001; OR = 1.78 95% CI 1.06–2.98; p = 0.03; I2 = 80%) (Fig. 3k).
Rosell Ortiz F., Fernández del Valle P., Knox E.C., Jiménez Fábrega X., Navalpotro Pascual J.M., Mateo Rodríguez I., et al. Influence of the Covid-19 pandemic on out-of-hospital cardiac arrest. A Spanish nationwide prospective cohort study. Resuscitation.
Survival to hospital admission, reported in six studies, occurred in 1739/6467 (26.9%) patients before the pandemic and 389/2168 (17.9%) during the pandemic (p < 0.001).
Rosell Ortiz F., Fernández del Valle P., Knox E.C., Jiménez Fábrega X., Navalpotro Pascual J.M., Mateo Rodríguez I., et al. Influence of the Covid-19 pandemic on out-of-hospital cardiac arrest. A Spanish nationwide prospective cohort study. Resuscitation.
Patients were more likely to survive to hospital admission before the pandemic (OR = 1.75 95% CI 1.42–2.17; p=<0.0001; I2 = 57%) (Fig. 3l). Similarly, survival to hospital discharge occurred in 551/6556 (8.4%) of patients before the pandemic and 141/2207 patients (6.4%) during the pandemic (p = 0.002), demonstrating that survival to hospital discharge occurred more frequently before the pandemic (OR = 1.65 95% CI 1.28–2.12; p < 0.001; I2 = 30%) (Fig. 3m).
Rosell Ortiz F., Fernández del Valle P., Knox E.C., Jiménez Fábrega X., Navalpotro Pascual J.M., Mateo Rodríguez I., et al. Influence of the Covid-19 pandemic on out-of-hospital cardiac arrest. A Spanish nationwide prospective cohort study. Resuscitation.
Across the selected studies, we observed a more than two-fold increase in OHCA incidence during the COVID-19 pandemic, with an overall significant increase in mortality. Our analysis found several disruptions to the chain of survival in OHCA victims during the pandemic and this may have at least in part contributed to the outcomes seen. There was reduced bystander CPR and AED use, along with increased supraglottic airway management by paramedic personnel. Also, time from call to ambulance arrival was longer during the pandemic.
The majority of OHCA was attributed to medical causes and was more frequently the reason for arrest. Public health measures may have role in reduction seen in the incidence of non-medical causes for OHCA. This is potentially due to a complex interplay of heightened financial difficulties, social isolation, uncertainty about the future, redistribution of the health workforce and the disruption to clinical services due to the pandemic-related lockdown, resulting in a delay in receiving care.
in 2020. Conversely, trauma causes of OHCA were less frequently observed, which is consistent with national lockdowns restricting mass gathering recreational and sporting events.
Mitchell R.D., O’Reilly G., Mitra B., Smit D.V., Miller J.-P., Cameron P.A. Impact of COVID-19 State of Emergency restrictions on presentations to two Victorian emergency departments. Emergency Medicine Australasia.n/a.
Despite most OHCA events occurring at home, a higher frequency of unwitnessed OHCA was observed. This may be explained by strict self-quarantine measures adopted, resulting in vulnerable populations such as the elderly being isolated from family members who would otherwise visit frequently. With “stay home” measures, it is unsurprising that significantly more cardiac arrests occurred at home, where quarantine isolation may have enforced living in different areas at home or different houses from family members.
It could be postulated that although OHCA events occurred at home where family may be present, they may be less likely to commence CPR due to psychological and emotional effects of the sudden event.
Although likely underreporting and/or identification of SARS-CoV-2 virus, the overall low prevalence of confirmed COVID-19 cases among OHCA during the pandemic suggests that any concerns regarding bystander CPR may be unwarranted especially in jurisdictions wherein risks of community transmission may be minimal. It should be noted, however, that CPR has the potential to generate aerosols
and safety of bystanders and pre-hospital healthcare workers is equally important. Community education, advanced healthcare planning and people wearing bands to indicate their wish not to receive CPR may go a long way in promoting dignity and comfort of the person who has suffered an OHCA and who has a poor chance of survival even outside a pandemic. During a pandemic it may of even greater relevance when health services are stretched, and an element of risk exists to responders providing CPR and ACLS.
There have been significant practice variations during the pandemic. For instance, there was an increase in use of supraglottic airway which may at least in part driven by risks of endotracheal intubation. The international liaison committee on resuscitation (ILCOR) recommends the use of supraglottic airways as first line for adults with OHCA (weak recommendation, very low certainty of evidence). However, the aerosol risks of supraglottic airway use when resuscitating patients with COVID-19 remian unclear anda supraglottic airway may potentially cause a false sense of security among healthcare providers.
Similarly, although ILCOR recommends the use of mechanical chest compression devices (weak recommendation, very low certainty of evidence), it is interesting to note that there was no difference in the use of mechanical CPR devices during the pandemic.
Interestingly, the frequency of a shockable rhythm/shocked events and ROSC was higher before the pandemic. This may reflect disruptions in the chain of survival, where the probability of ROSC diminishes significantly with time and it is unclear whether increased non-shockable rhythm is a consequence of delayed response or underlying pathophysiology.
Additionally, this may be related to the delay from call to ambulance arrival that is observed in this study. The quantitative increase in OHCA calls and the need to properly apply personal protective equipment and disinfect ambulances between calls likely contributed to the delay in response and regrettably contributed to the observed increase in OHCA mortality.
This may also be compounded by the increased frequency of unwitnessed OHCA and reduction in bystander CPR. As a result, patients may be found long after cardiac arrest where they may no longer be in a shockable rhythm.
The absolute increase in OHCA incidence and corresponding rise in mortality was reported in our analysis. Direct COVID-19 deaths would account for a proportion of these deaths,
Characteristics associated with out-of-hospital cardiac arrests and resuscitations during the novel coronavirus disease 2019 pandemic in New York City.
while indirect factors such as lockdown and behavioral changes for fear of infection or reluctance to burden health systems may have resulted in delays in presenting to hospital.
Worldwide, a decrease in acute hospital presentations have been observed, with reports of reduced ST-elevation myocardial infarction presentations in Spain, Italy and USA.
There are several limitations that need to be acknowledged. Firstly, most of the included studies were from the early phase of the pandemic from countries that were significantly affected and had little time to prepare. Moreover, some degree of lockdown in many of the countries, due to the fear of contracting the virus, which implied that many people continued to avoid health care facilities. Hence the result may still be representative during the pandemic. Secondly, postmortem testing to confirm COVID-19 was not reported, hence the direct causation of COVID-19 infection and OHCA or its indirect association due to unattended comorbid diseases during this pandemic was not readily available. Thirdly, there was limited information about the previous medical history or comorbidities of these OHCA patients. Finally, it would been helpful to map the OHCA event curve against that of the epidemiological pandemic curve (based upon hospital confirmed cases) in each of the reporting areas to observe any correlations between the incidence of COVID-19 and OHCA event rates, however this data was not provided in the studies. This information would be critical in helping systems better prepare for future resurgences in COVID-19 cases.
Conclusion
The incidence and mortality of OHCA during the COVID-19 pandemic was significantly higher as compared to time periods before the pandemic. Multiple factors may have contributed to the increased mortality, including increased time from call to ambulance arrival and the reduced frequency of unwitnessed events, bystander CPR and AED use. There were significant practice changes during the pandemic. Urgent research to improve pre-hospital care during a pandemic is required.
Author contributions
Zheng Jie Lim: This author has conceived the project idea, conducted the systematic review, statistical analysis, assisted with data analysis, wrote the initial drafts of the manuscript, created tables and figures and finalized the manuscript.
Mallikarjuna Reddy: This author has conducted the systematic review, assisted with data analysis, wrote the initial drafts of the manuscript and finalized the manuscript.
Afsana Afroz: This author has conducted the statistical analysis, created the figures and wrote the statistical section in methods.
Baki Billah: This author has conducted the statistical analysis, created the figures and wrote the statistical section in methods.
Kiran Shekar: This author has analyzed the data, edited and critically evaluated the manuscript and finalized the manuscript.
Ashwin Subramaniam: This author has conducted the systematic review, statistical analysis, assisted with data analysis, wrote the initial drafts of the manuscript, created tables and figures and finalized the manuscript.
All authors critically reviewed the manuscript and approved the final version prior to submission.
Funding
No funding sources to declare.
Competing interests
All authors declare no support from any organization for the submitted work, no competing interests with regards to the submitted work
Declaration of Competing Interest
The authors report no declarations of interest.
Acknowledgements
Prof Shekar acknowledges research support from Metro North Hospital and Health Service. We would like to acknowledge the work of pre-hospital health professionals in providing excellent health care during the COVID-19 pandemic.
Appendix A. Supplementary data
The following are Supplementary data to this article:
Characteristics associated with out-of-hospital cardiac arrests and resuscitations during the novel coronavirus disease 2019 pandemic in New York City.
GA Wells BS, D O’Connell, J Peterson, V Welch, M Losos, P Tugwell. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses.
Rosell Ortiz F., Fernández del Valle P., Knox E.C., Jiménez Fábrega X., Navalpotro Pascual J.M., Mateo Rodríguez I., et al. Influence of the Covid-19 pandemic on out-of-hospital cardiac arrest. A Spanish nationwide prospective cohort study. Resuscitation.
Mitchell R.D., O’Reilly G., Mitra B., Smit D.V., Miller J.-P., Cameron P.A. Impact of COVID-19 State of Emergency restrictions on presentations to two Victorian emergency departments. Emergency Medicine Australasia.n/a.
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