Clinical Investigations External Validation of Multimodal Termination of Resuscitation Rules for Out-of-hospital Cardiac Arrest Patients in the Covid-19 Era

doi:10.21203/rs.3.rs-32324/v1

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Clinical Investigations External Validation of Multimodal Termination of Resuscitation Rules for Out-of-hospital Cardiac Arrest Patients in the Covid-19 Era

https://doi.org/10.21203/rs.3.rs-32324/v1

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published 27 Jan, 2021

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Background:Futile resuscitation for out-of-hospital cardiac arrest (OHCA) patients in the COVID-19 era can lead to risk of disease transmission and unnecessary transport. Various existing basic or advanced life support (BLS or ALS) rules for termination of resuscitation (TOR)have been derived and validated in North America and Asian countries. This study aimed to evaluate the external validation of these rules in predicting the survival outcomes of OHCA patients in the COVID-19 era.

Methods: A multicenter observational study was performed using the WinCOVID-19 Daegu registry data collected from 18 February to 31March 2020. The outcomes of each rule were compared to the actual patient survival outcomes. The sensitivity, specificity, false positive ratio (FPR), and positive predictive value (PPV) of each TOR rule were evaluated.

Results: Of the 184 OHCA patients, 170 patients,who showed cardiac arrest of presumed cardiac etiology, were enrolled. TOR was recommended for 122 patientsbased on the international BLS-TOR rule, which showed 85% specificity, 74% sensitivity, 0.8% FPR, and 99% PPV for predicting unfavorable survival outcomes. When the traditional BLS-TOR rules and KoCARC TOR rule II were applied to our registry, one patient met the TOR criteria but survived at hospital discharge. With regard to the FPR (upper limit of 95% confidence interval<5%) and PPV (>99%) criteria, only the KoCARCTOR rule I, which included a combination ofthree factors including not being witnessed by emergency medical technicians, presenting with an asystole at the scene, and not experiencing prehospital shock delivery or ROSC, was found to be superiorto all other TOR rules.

Conclusion: Among the previous nine BLS and ALS TOR rules, KoCARCTOR rule I was most suitable for predicting poor survival outcomes and showed improved diagnostic performance. Further research on variations in resources and treatment protocols among facilities, regions, and cultures will be useful in determining the feasibility of TOR rules for COVID-19 patients worldwide.

Trial registration: Not applicable

Critical Care & Emergency Medicine

Heart arrest

Prognosis

Coronavirus disease

Ethics

Cardiopulmonary resuscitation

We are still fighting the novelcoronavirusdisease (COVID-19) at the forefront worldwide [1].Due to the symptoms and complications that individuals presentwith and transmission efficiency of COVID-19, we changedour standard treatment processes and personal protection strategies. In particular, resuscitation of cardiac arrest patients posed an especially high risk of transmissionof disease to healthcare professionals [2,3].For in-hospital cardiac arrest (IHCA) patients, this procedure wastypically performedafter COVID-19 had been confirmed, but for out-of-hospital cardiac arrest (OHCA) patients, resuscitationwas performed prior to any testing or confirmation. Consequently, the OHCA group was especially vulnerable.

In the prehospital setting, emergency medical personnel screened patients for COVID-19 based on their symptoms (fever, dyspnea, cough, and sore throat) and inquired about any recent historyof contact with infected individuals. However,this method was not always ideal because many carrierswere asymptomatic [4,5].As such, personal protective equipment (PPE) and medical resources in intensive care units (ICUs)were not alwaysutilized by physicians who tended to COVID-19 patients, andpatients who failed to experience a return of spontaneous circulation (ROSC) in the event of a cardiac arrest were often not transferred to a hospital due to the low likelihood of their survival [6]. Fortunately, recent cardiopulmonary resuscitation (CPR) guidelineswere changed, recommendingthat all healthcare providers assess the safety of the scene and wear higher levels of PPE for protection against infectious airborne dropletsand detailing the criteria for the basic life support termination of resuscitation (BLS-TOR) rule. These guidelines stated that before terminating resuscitative efforts, the healthcare workers must check that 1) the arrest was not witnessed byemergency medical service (EMS) personnel or a first responder,2)ROSC was not observed prior to the patient being transported to the emergency medical centre (EMC), and 3) no electrical shocks were delivered [7-14].

We applied the rules that were typically selected depending on the country or region where the derivation and validation phaseswere conducted.These included the(1) International BLS and advanced life support (ALS) rules derived and validated in the United States and Europe [8], (2) Goto and KANTO-SOS rules developed in Japan and Asian countries [13,14], and (3) Korean OHCA registry-based TOR models,Korean Cardiac Arrest Research Consortium (KoCARC) TOR rules, and two new TOR models, whichwere used in our previous studies [7,11].

In Daegu metropolitan city, the number of patients with COVID-19 increased rapidlyat the community level fromFebruary 18, 2020, in response to the pandemic outbreak in South Korea.During its 7-week peak, we resuscitated 184 OHCA patients at six EMCs. This was the first study to determine the efficacy of these TOR guidelinesfor an emerging infectious disease [7,11,12].

Enrolled OHCA patients

Daegu is a metropolitan city with a population of 2.44 million people, and is composed of two regional level I EMCs, four local level II EMCs, and 19 emergency facilities or clinics. In particular, there are six EMCs where ALS, post-cardiac arrest care, and cardiovascular interventions are available. Patients (>18 years old) whopresented with presumed OHCA and used the EMS system in Daegu were included in the study. Those who did not receive any resuscitationand those who experienced cardiac arrest in a primary care clinic or long-term care hospital were excluded. From 18 February 2020 to 31 March 2020 (the peak of the COVID-19 outbreak), 184 adults developed OHCA.Of them, 170patients were included in this study (Fig. 1). The study was approved by the Institutional Review Board ofKyungpook National UniversityHospital.(KNUH 2020-04-032)

Study design and variables

We conducted a multicenter observational study using the WinCOVID-19 citywide OHCAregistry dataand evaluated patient demographics (age andsex), prehospital variables (place of arrest, initial cardiac rhythm,whether it was witnessed by a bystander or EMS personnel,whether a bystander performed CPR, whether an automated external defibrillator (AED) was used and prehospital defibrillation occurred, and whether ROSC occurred), and time intervals (response time was defined as the period from contactingthe EMS to themarrivingat the scene,while scene time was defined as the period fromthe EMS arrivingat the scene to themdeparting from the scene). Resuscitation management and survival outcomes (including ROSC, survival to admission, survival to discharge,and neurological outcomes at discharge) aftercardiac arrest were recorded as hospital-level variables. Based on this collective data, we determined whether the patients met the existing TOR guidelines and qualified to be enrolled in this study. In South Korea, EMS personnel cannot terminate resuscitation unless OHCA patients show obvious signs of death [7,11];therefore, all EMS-treated OHCA patients should be transported to the hospitals.Notably, these personnel use manual defibrillators and analyze electrocardiograms(ECGs) prior tothe patients’ arrival at the hospital.

Toevaluate COVID-related variables, we obtained data, including the clinical symptoms or signs, vital signs (fever[defined as a temperature of 37.5°C or higher], sore throat, and cough), recent exposure history, and chest X-ray findings, of patients with confirmed COVID-19 from electronic medical records on admission.

Main outcome measures

Primary outcome measures were based on the proportions of survival to hospital discharge (defined as discharged to go home or transferred to another facility after admission to the hospital) and survival with a favorable neurological outcome (quantified using Cerebral Performance Category scores, with scores of 1 and 2 being the most favorable) in the group.

Secondary outcome measures included external validation of previously researched TOR rules (Table 1). We delineated OHCA patients who met all the TOR criteria and calculated sensitivity, specificity, false positive ratios (FPR), false negative ratios, positive predictive values (PPV), negative predictive values (NPV), and their respective 95% confidence intervals (CI) to identify patients with a risk of poor survival [7,8,11,13,14].

Table 1

Criteria of the BLS-TOR and KoCARCBLS-TOR rules
TOR rules	Witness status	Initial prehospital rhythm	Prehospital shock	Prehospital ROSC	Others
Based on prehospital criteria
International BLS rule⁸	not witnessed by EMT		no prehospital shock	no prehospital ROSC
International ALS rule⁸	not witnessed by bystander/EMT		no prehospital shock	no prehospital ROSC	no bystander CPR
Goto’s TOR rule¹³	not witnessed by bystander	Initial non-shockable rhythm		no prehospital ROSC
KoCARC TOR rule I ⁷	not witnessed by EMT	asystole in prehospital conditions	no prehospital shock	no prehospital ROSC
KoCARC TOR rule II	not witnessed by EMT		no prehospital shock	no prehospital ROSC	Age>60
KoCARC TOR rule III	not witnessed by EMT	asystole in prehospital conditions	no prehospital shock	no prehospital ROSC	Age>60
New TOR model 1¹¹	not witnessed by bystander	asystole in the field		no prehospital ROSC
Based on prehospital and ED
SOS-KANTO’s TOR rule¹⁴	not witnessed by bystander	asystole in the field			asystole in the hospital
New TOR model 2	not witnessed by bystander			no prehospital ROSC	asystole in the hospital
ALS, advanced life support; BLS-TOR: basic lifesupport and termination of resuscitation; CPR, cardiopulmonary resuscitation;EMT, emergency medical technicians; KoCARC, Korean Cardiac Arrest Research Consortium; ROSC, return of spontaneous circulation; SOS-KANTO: survey of survivors after cardiac arrest conducted in the Kanto area in 2012 (2017)

Statistical analyses

All data were analyzed using IBM SPSS Statistics v. 25 (IBM Corp., Armonk, NY, USA) and MedCalc v. 17.4.4 (MedCalc Software, Mariakerke, Belgium). The normality of the variables was determined using the Shapiro–Wilk test. Descriptive statistics were presented as medians with interquartile ranges (IQR, 25th and 75th percentiles), and categorical variables were presented as amounts and percentages. Significant differences among the survival outcomes weredetermined using the Mann-Whitney test for continuous variables and chi-square tests or Fisher’s exact test for categorical variables.

Logistic regressions were performed for patients who met the criteria of the previous TOR rules. The outcome of interest was survival to hospital discharge(Table 1). To determine the model calibration, the Hosmer-Lemeshow goodness of fittest was calculated. Odds ratio (OR) greater than 1 indicatedan unfavorable effect on survival; ORs and 95% CIs were calculated for all covariates. The characteristics of the adjusted ORswere described using Forest plots. A receiver operating characteristic (ROC) curve, with the area under the curve (AUC), was used to determine the accuracy of such variables in predicting unfavorable survival outcomes at discharge. All tests were two-tailed, and p<0.05 was considered statistically significant.

Diagnostic performances of allexistingTOR rules were calculated. Previous TOR rules were created based on FPR (the probability that the rule will suggest terminating resuscitation in case of patient survival) and PPV (the probability that the rule will suggest terminating resuscitation in case of patient death) of the rules. Current guidelines recommend that when cessation of life-sustaining care is considered, the tool used to predict poor outcomes must be accurate and reliable with an FPR (close to 0%) with a narrow 95% CI (0%-10%). PPV must be greater than 99% [7,15].Imprecision was graded as ‘serious’ when the upper limit of the 95% CI for FPR was greater than 5% and ‘very serious’ when thesame value was greater than 10%. Medical futility and drug therapy were found to impart a less than 1% chance of survival.

Patient characteristics

Of the 170 patients, 63.2% were men, 76.0% was witnessed by EMS personnel, 34.3% received CPRfrom a bystander, 4.7% experienced ROSC prior to hospital arrival, 58.5% showed abnormal chest X-rays,and 5.8% were confirmed to have COVID-19 by reverse transcription polymerase chain reaction(RT-PCR). All baseline characteristics of the study population are summarized in Table 2.

Table 2

General characteristics of the COVID-19 OHCA study population
	Overall (n=170)	Survival at discharge (n=7)	Dead (n=163)	P value
Age (years), median [IQR]	74 [62-80]	62 [57-69]	75 [63-80]	0.027
Age more than 70 years	101 (59.4)	1 (14.3)	100 (61.3)	0.018
Male sex	108 (63.5)	5 (71.4)	103 (63.2)	0.996
COVID-19 related
Previous COVID-19 dx before OHCA	3 (1.8)	0 (0)	3 (1.8)	0.999
Presumed symptoms before OHCA	20 (11.8)	1 (14.3)	19 (11.7)	0.591
chest PA after CPR	140 (82.4)	7 (100)	133 (81.6)	0.356
Abnormal chest x-ray findings	100 (58.8)	5 (71.4)	95 (58.3)	0.701
Acquired RT-PCR test	80 (47.1)	5 (71.4)	75 (46.0)	0.258
Final confirmation of COVID-19	10 (5.9)	0 (0)	10 (6.1)	0.999
Comorbidities
Diabetes mellitus	52 (30.6)	2 (28.6)	50 (30.7)	0.999
Hypertension	59 (34.7)	3 (42.9)	56 (34.4)	0.695
Chronic renal disease	8 (4.7)	1 (14.3)	7(4.3)	0.291
Malignancy, cancer	28 (16.5)	0 (0)	28 (17.2)	0.601
COPD, asthma	6 (3.5)	0 (0)	6 (3.7)	0.997
Heart failure, ischemic heart disease	26 (15.3)	0 (0)	26 (16.0)	0.597
Dementia, Parkinson disease	18 (10.6)	0 (0)	18 (11.0)	0.998
ICH, ischemic stroke	16 (9.4)	1 (14.3)	15 (9.2)	0.506
Liver cirrhosis, and others	17 (10.0)	0 (0)	17 (10.4)	0.998
Location of OHCA, public place	49 (28.8)	4 (57.1)	45 (27.6)	0.107
Prehospital parameters
Witnessed event, anyone	129 (75.9)	6 (85.7)	123 (75.5)	0.994
Prehospital mechanical CPR	134 (78.8)	5 (71.4)	129 (79.1)	0.640
Prehospital defibrillation	22 (12.9)	3 (42.9)	19 (11.7)	0.047
Time variables, median [IQR]
Response time interval (min)	8 [6-10]	8 [7-9]	8 [6-10]	0.743
Scene time interval (min)	21 [15-26]	15 [13-25]	22 [16-27]	0.205
Prehospital ROSC before ED arrival	8 (4.7)	6 (85.7)	2 (1.2)	<0.001
COPD, chronic obstructive pulmonary disease; CPR, cardiopulmonary resuscitation; ED, emergency department; ICH, intracerebral hemorrhage; IQR, interquartile ranges; OHCA, out-of-hospital cardiac arrest; ROSC, return of spontaneous circulation; RT-PCR, reverse transcription polymerase chain reaction

Factors associated with survival

The rate of survival to discharge was 4.7%, and that of survival with favorable neurological outcomes was 2.9%. In general,survivors, compared to the patients who died, were younger, experienced more prehospital defibrillations, and achieved ROSC before arriving at theemergency department (ED) (Table 2). Advanced age, not being witnessed by EMT personnel, receiving no shocks,and not developing ROSC before arrivingat the ED were factors related to unfavorable survival outcomes. Only ROSC before arriving at the ED was related to survival to discharge (Fig. 2). Interestingly, age, witness status, and prehospital shock delivery were significantly associated with survival outcomes in the univariate analysis, but not in the multivariable analysis (Table 3).

Table 3

Logistic regressions of factors associated with unfavorable survival outcomes
			Univariate		Multivariable^*
	Dead	Survival	Crude Odds (95% CI)	P value	Adjusted Odds (95% CI)	P value
Age (years)	75 [63-80]	62 [57-69]	1.05 (1.00-1.10)	0.070
Age >70 years	100 (61.3)	1 (14.3)	9.52 (1.12-80.97)	0.039	6.43 (0.28-148.0)	0.244
Age >60 years	127 (77.9)	4 (57.1)	2.64 (0.56-12.36)	0.216	0.44 (0.02-8.83)	0.591
Location, non-public places	118 (72.4)	3 (42.9)	3.49 (0.75-16.24)	0.107
Not witnessed by bystander	64 (39.3)	3 (42.9)	0.86 (0.18-3.97)	0.999
Not witnessed by EMT	139 (85.3)	4 (57.1)	4.34 (0.91-20.63)	0.081	1.56 (0.06-39.89)	0.782
No bystander CPR	108 (66.3)	4 (57.1)	1.47 (0.32-6.81)	0.691
Initial acquiredrhythm
Non-shockable rhythm in the field	152 (93.3)	3 (42.9)	18.42 (3.65-92.8)	0.001	15.32 (0.04-663.7)	0.378
Asystole in the field	107 (65.6)	0 (0)	-	0.001	-
Asystole in the ED	127 (77.9)	0 (0)	-	<0.001	-
No prehospital shock delivery	144 (88.3)	4 (57.1)	5.68 (1.18-27.4)	0.047	6.06 (0.26-101.1)	0.262
No prehospital ROSC	161 (98.8)	1 (14.3)	48.30 (3.83-109.3)	<0.001	26.24 (1.48-463.3)	<0.001
CI, confidence interval; CPR, cardiopulmonary resuscitation; ED, emergency department; EMT, emergency medical technician; OR, odds ratio; ROSC, return of spontaneous circulation ^*Adjusted for age, gender, location of arrest, primary electrocardiogram (ECG), witness status, and whether prehospital ROSC was achieved before arriving at the ED

External validation of the TOR rules

On applying the existing internationalTOR rules to our registry, we found that 122 patients (71.8%) met all three criteria,but one survivor was discharged (Fig. 1).Another patient met the criteria for the traditional BLS-TOR andKoCARC TOR II rules, buthetoo was discharged(Table 4). The ROC curves of multimodal TOR categories for poor outcomesare shown in Figure 2. Overall, KoCARC TOR rule I and the currentTOR rule II, with AUCs of 0.951 and 0.967, respectively,could be used most effectivelyfor predicting in-hospital mortality (Fig. 3). In terms of the criteria of FPR (upper limit of 95% CI <5%) and PPV (>99%), only KoCARC TOR rule I could be used to predict poor survival outcomes, and it showed a higher diagnostic performance than the other TOR rules (Table 4).

Table 4

External validations of multimodal TOR rules for predicting death prior to discharge (n=170)
TOR rules		Death	Survival	Sensitivity (95% CI)	Specificity (95% CI)	FPR (95% CI)	PPV (95% CI)	NPV (95% CI)
Before arriving at the ED
International BLS-TOR	met all criteria	121	1	74.2%	85.7%	0.8%	99.2%	12.5%
	did not fulfill	42	6	(66.7-80.6)	(42.0-99.2)	(0.04-5.2)	(84.8-99.9)	(5.2-25.9)
Goto’s rule	met all criteria	58	0	35.6%	100%	0%	100%	6.3%
	did not fulfill	105	7	(28.4-43.5)	(56.1-100)	(0-7.7)	(92.3-100)	(2.8-12.9)
KoCARC TOR rule I	met all criteria	93	0	57.1%	100%	0%	100%	9.1%
	did not fulfill	70	7	(49.1-64.7)	(56.1-100)	(0-4.9)	(95.1-100)	(4.0-18.4)
KoCARC TOR rule II	met all criteria	97	1	56.5%	85.7%	1.0%	98.9%	8.3%
	did not fulfill	66	6	(51.5-67.0)	(42.0-99.2)	(0.05-6.4)	(93.6-99.9)	(3.4-17.9)
KoCARC TOR rule III	met all criteria	78	0	47.9%	100%	0%	100%	7.6%
	did not fulfill	85	7	(40.0-55.8)	(56.1-100)	(0-5.8)	(94.2-100)	(3.4-15.6)
New TOR Model 1	met all criteria	35	0	21.5%	100%	0%	100%	5.2%
	did not fulfill	128	7	(15.6-28.7)	(56.1-100)	(0-12.3)	(87.7-100)	(2.3-10.8)
After ED arrival
International ALS TOR	met all criteria	23	0	14.1%	100%	0	100%	4.8%
	did not fulfill	140	7	(9.3-20.6)	(56.1-100)	(0-17.8)	(82.2-100)	(2.1-9.9)
SOS-KANTO’s rule	met all criteria	33	0	20.2%	100%	0%	100%	5.2%
	did not fulfill	130	7	(14.5-27.4)	(56.1-100)	(0-12.9)	(87.0-100)	(2.3-10.6)
New TOR Model 2	met all criteria	45	0	27.6%	100%	0%	100%	5.6%
	did not fulfill	118	7	(21.0-35.2)	(56.1-100)	(0-9.7)	(90.2-100)	(2.4-11.6)
ALS, advanced life support; BLS-TOR,basic life support and termination of resuscitation; CI, confidence interval; ED, emergency department; FPR, false positive rate; KoCARC, Korean Cardiac Arrest Research Consortium;NPV, negative predictive value; PPV, positive predictive value; SOS-KANTO: survey of survivors after cardiac arrest conducted in the Kanto area in 2012 (2017)

In this study, we validatedthe existingmultimodal TOR rules using the WinCOVID-19 Daegu registry data on OHCA patients.This was the first study to determine the efficacy of these TOR guidelinesfor an emerging infectious disease.Among the nine existing TOR rules, KoCARC TOR rule I, having the lowest FPRand highest PPV, was found to be the best indicator of poor outcomes during the COVID-19 outbreak.

Resuscitation of infected individuals greatly increases the risk of transmission of virus to healthcare providers [1,6,16]. According to the guidelines, emergency personnel are recommended to confirm the presence of COVID-19 in OHCA patients and wear high-level PPE and perform CPR. They must wear PPE, even when in doubt. However, this new type of corona infection has a very high rate of disease transmission and is characterized by approximately 25% of asymptomatic infection [4]; therefore, the COVID-19 era was a confusing time for healthcare workers in the many medical and emergency fields [5]. Some OHCA patients were unexpectedly confirmed to be positive post-CPR or on performing postmortem,contributing to emergency room shutdown and temporary closure [17].As of April 2020, more than 10,000 people have been confirmed to have COVID-19 and 167 COVID-19 patients have died in South Korea. More than 70% of these cases occurred in Daegu, the area of interestin this study, and Gyeongbuk, the neighboring area [10].More than 130 cases of infected healthcare workers and medical staff have been reported.One physician died while treating two confirmed patients.

Our findings, although preliminary, showed that survival outcomes of OHCA patients in Daegu during the peak of the COVID-19 outbreak (4.1%) were significantly lower than those reported nationwide (9.8%) or in the city (8.8%) in 2018 [18]. We could not describe the broken chain of survivaland the negative effects on high-quality CPR in the results of the present study;however, due to this pandemic, the risk-benefit balance for CPRshould be reconsidered[2].Other studies have also raised the question of how CPRmust be performed for IHCA patients with confirmed COVID-19.Considering the lower survival rate, physicians should be concerned about the goals of care or CPR preferences to reduce futile resuscitation by stratifying survivability of the IHCA patients, regardless of their COVID-19 status, at the time of hospital admission [5,19]. It was also important to consider prehospital TOR for out-of-hospital resuscitation in an infectious disease epidemic area.

The previously existing TOR rules can be divided into two combined sets of variables, one of which can be applied at the pre-hospital level and the other can be evaluated immediately after arriving at the ED. In this study, we selected and analyzed the external validation of all nine multimodal TOR rules for OHCA patients during the COVID-19 epidemic period. These rules were typically selected depending on the country or region where the derivation and validation phaseswere conducted.These included the(1) International BLS(acombination of three criteria, including not being witnessed by emergency medical technicians (EMT), not receiving prehospital shock delivery, and not experiencing prehospital ROSC, see Table 1) and ALS rules derived and validated in the United States and Europe [8], (2) Goto and KANTO-SOS rules developed in Japan and Asian countries [13,14], and (3) Korean OHCA registry-based TOR models, KoCARC TOR rules, and two new TOR rules, which were used in our previous studies [7,11]. The international BLS-TOR rules that can be enforced at the prehospital stage show high sensitivity and specificity, but also relatively high FPR (upper limit of 95% CI of FPR>5%) [9,15];therefore, continuous development of the TOR model has been proposed [7,9].The researchers also proposed a new TOR model 1 that was applicable at the prehospital stage and a new TOR model 2 that was applicable immediately after arriving at the ED in previous studies by including acquired ECG asystole rhythm as a criterion [11].

The previous four rules have been partially validated in other countries and in the setting of mechanical CPR or comprehensive post-resuscitationcare [12,20-23]. Previous validations of the TOR rule reported survival rates of less than 1% among TOR rule–positive patients in North America; however, high FPR of survival has been reported in Asian countries (28.7% in Singapore, 25.9% in Taiwan, and 30.4% in South Korea). This discrepancy may be due to different prehospital practices and a relatively higher prevalence of non-shockable rhythm in patients in Asian countries [7]. However, high FPRs of survival in these Asian countries, where the withdrawal of life-sustaining treatment is not commonly applied, are likely to be biased. Kajino et al. [24]validated the TOR rules for predicting poor neurologic outcomes in a Japanese population and concluded that more specific TOR rules for each region should be developed, despite the good performance of the TOR rules in their study. However, even if the COVID-19 outbreak was not taken into account, these previous results implied that the extrapolation to and implementation of different TOR rules in regions with different organization of EMS treatment protocols, legislation, and socioeconomic characteristics might be problematicbecause the TOR rules would need to be adjusted to meet the regional situation.

In this study, we validatedthe existing multimodal TOR rules using the WinCOVID-19 Daegu registry data on OHCA patients. Based on the results of our study, we failed to screen one survivor, out of the seven survival discharges out of 170 OHCA patients, for the international BLS and KoCARC II rules; however, the remaining seven TOR rules were classified correctly. Based on current guidelines, it is recommended that diagnostic tests that guidethe cessation of life-saving efforts be accurate and reliable and show an FPR value close to 0% [7,9].Among the nine rules,KoCARC TOR rule I,showing the lowest FPR (upper limit of 95% CI <5%) and highest PPV (>99%), was found to be the most effective indicator for poor outcomes. This rule included the combinationof three factors, including not being witnessed by EMT, presenting with an asystole at the scene, and experiencing no prehospital shock or ROSC. It did not include the patient’s age or ED parameters, thereby being easyto use in prehospital settings and applicable for OHCA patients in this current pandemic [7].

This studyhad several strengths and limitations. First, as with other multicenter observational studies,this study showed that the integrity of the data could be biased. Additionally, our observation period lasted onlytwo months;hence, the effects on long-term survival outcomes, which are most important for OHCA research, remain unknown. In this regard, we will continue to conduct investigations until COVID-19 has been effectively tackled. Second, it has been speculated thatpoor survival outcomes areassociatedwithfewer resuscitationsand prolonged EMS scene and transport timeto the hospital. Moreover, unfavorable neurological outcome, as a primary outcome,is more suitable than survival to discharge. Since only four patients in our study displayedfavorable neurological outcomes, we could not perform any secondary analyses or external validations. Third, the ratio of the survival outcomes was much lower in our study thanin previous Korean OHCA data reports developed during the COVID-19 outbreak, and it is possible that this was due tothe direct adverse effects of COVID-19 on the cardiovascular system, prolonged EMS scene time,and differences in treatment in different hospitals [25]. Finally, facility or regional differences in EMS resources, CPR quality, and post-cardiac arrest care might affect the survival outcomes during the COVID-19 outbreak. TOR rules in the COVID-19 era and socio-ethical issues must be discussed further, and a consensus process must be developed.

Among the nine previouslyexisting TOR rules, KoCARCTOR rule I was found to be the most suitable for predicting poor survival outcomes, and it showed improved diagnostic performance in the COVID-19 era. With regard tothe FPR and PPV criteria, KoCARCTOR rule I, which included a combination of three factors including not being witnessed by EMT, presenting with an asystole at the scene, andexperiencing no prehospital shock or ROSC,was superior toall other TOR rules.Further research on variations in resources andtreatment protocols (CPR quality and post-cardiac arrest care) among facilities, regions, andcultures will be useful in determining the feasibility of TOR rulesfor COVID-19 patients worldwide.

COVID-19: novel coronavirus disease; IHCA: in-hospital cardiac arrest; OHCA: out-of hospital cardiac arrest; PPE: personal protective equipment; ICU: intensive care unit; ROSC: return of spontaneous circulation; CPR: cardiopulmonary resuscitation; BLS-TOR: basic life support termination of resuscitation; EMS: emergency medical service; EMC: emergency medical centre; ALS: advanced life support; KoCARC: Korean Cardiac Arrest Research Consortium; AED: autumated external defibrillator; ECG: electrocardiogram; FPR: false positive ratio; PPV: positive predictive value; NPV: negative predictive value; CI: confidence interval; IQR: interquartile range; OR: odds ratio; ROC: receiver operating characteristic; AUC: area under the curve; RT-PCR: reverse transcription polymerase chain reaction; ED: emergency department; EMT: emergency medical technician

Ethical approval and consent to participate

The study was approved by the Institutional Review Board (IRB ) of Kyungpook National University Hospital.(KNUH 2020-04-032)

Consent for publication

Not applicable

Availability of data and materials

The data that support the finings of this study are available from the corresponding author upon reasonable request.

Competing interests

The authors have no potential conflicts of interest to disclose.

Funding

This study has received no funding.

Author contributions

All authors has a substantial contribution in terms of study design, data collection, data interpretation and manuscript writing. The authors read and approved the final manuscript.

Acknowledgments

Not applicable

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Clinical Investigations External Validation of Multimodal Termination of Resuscitation Rules for Out-of-hospital Cardiac Arrest Patients in the Covid-19 Era

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Abstract

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Background

Methods

Enrolled OHCA patients

Study design and variables

Main outcome measures

Statistical analyses

Results

Patient characteristics

Factors associated with survival

External validation of the TOR rules

Discussion

Limitations

Conclusions

List Of Abbreviations

Declarations

Ethical approval and consent to participate

Consent for publication

Availability of data and materials

Competing interests

Funding

Author contributions

Acknowledgments

References

Status:

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