Abstract
Objective:
The proportion of sudden cardiac arrests (SCA) manifesting with pulseless electrical activity (PEA) has increased significantly, and the survival rate remains lower than ventricular fibrillation (VF). However, a subgroup of PEA-SCA cases does survive and may yield key predictors of improved outcomes when compared to non-survivors. We aimed to identify key predictors of survival from PEA-SCA.
Methods:
Our study sample is drawn from two ongoing community-based, prospective studies of out-of-hospital SCA: Oregon SUDS from the Portland, OR metro area (Pop. approx. 1 million; 2002–2017) and Ventura PRESTO from Ventura County, CA (Pop. approx. 850,000, 2015–2021). For the present sub-study, we included SCA cases with PEA as the presenting rhythm where emergency medical services (EMS) personnel attempted resuscitation.
Results:
We identified 1,704 PEA-SCA cases, of which 173 (10.2%) were survivors and 1,531 (89.8%) non-survivors. Patients whose PEA-SCA occurred in a healthcare unit (16.9%) or public location (18.1%) had higher survival than those whose PEA-SCA occurred at home (9.3%) or in a care facility (5.7%). Young age, witness status, PEA-SCA location and pre-existing COPD/asthma were independent predictors of survival. Among witnessed cases the survival rate was 10% even if EMS response time was >10 minutes.
Conclusions:
Key determinants for survival from PEA-SCA were young age, witnessed status, public location and pre-existing COPD/asthma. Survival outcomes in witnessed PEA cases were better than expected, even with delayed EMS response.
Keywords: Sudden Cardiac Arrest, Pulseless Electrical Activity, Survival, general population, asthma, copd, hypoxia
Introduction
Despite the recent progress in the prevention and treatment of cardiac disease, out-of-hospital sudden cardiac arrest (SCA) is a major cause of mortality worldwide, resulting in more years of potential life lost than any individual cancer(1). SCAs can manifest with either shockable (ventricular fibrillation [VF] and ventricular tachycardia [VT]) or non-shockable (pulseless electrical activity [PEA] and asystole) rhythms. A significant amount of effort has been put into treating and preventing shockable SCAs, while non-shockable SCAs have received less attention. Shockable rhythms were dominant forty years ago, but the proportion of shockable SCAs has declined in recent decades, and currently the majority of SCAs (70–80%) present with non-shockable rhythms(2, 3).
Thirty years ago, asystole and PEA were addressed separately in advanced life support guidelines(4). More recently, asystole and PEA have been treated collectively as non-shockable SCA in the current resuscitation guidelines(5, 6). Similarly, outcomes from PEA and asystole have often been reported collectively as non-shockable SCA (7, 8), but some studies have reported that PEA has a better prognosis than asystole(9, 10). Moreover, PEA and asystole are likely to have distinct etiologies and pathophysiologies (11–16). Given the wide spectrum of clinical profiles and hemodynamic states in cardiac PEA (17, 18), survival rates among PEA-SCA cases are also likely to vary. A better understanding of key predictors of survival may have the potential to translate into improved resuscitation success and better PEA-SCA survival outcomes. In the present study, we utilized data from two large prospective and community-based SCA cohorts to identify key predictors of survival from PEA-SCA.
Methods
Population cohorts (Oregon SUDS and Ventura PRESTO)
Our study population is drawn from two different studies in the United States: the Oregon Sudden Unexpected Death Study (Oregon SUDS, since 2002) and the Ventura Prediction of Sudden Death in Multi-Ethnic Communities study (Ventura PRESTO, since 2015). Both studies use an identical design, and previous studies have described the study protocols in more detail(1, 19, 20). Both Oregon SUDS and Ventura PRESTO are prospective and ongoing community-based studies that have ascertained all out-of-hospital SCAs from the Portland Oregon metro area (population ~1 million), and Ventura County (population ~850,000), respectively. Studies identify out-of-hospital SCAs using data from regional hospitals, the state Medical Examiner’s office, and the regions’ 2-tiered Emergency Medical Services (EMS) systems. Trained physician-researchers performed an in-house SCA adjudication for each potential SCA case, using all available medical data: medical records from the regions’ hospital systems, medical examiner’s reports, and EMS reports. In both studies, SCA was defined as a witnessed sudden loss of pulse of likely cardiac etiology, or if unwitnessed, the subject should have been seen alive within 24 h in a good state of health. Cases with likely non-cardiac SCA etiology (e.g., intoxication, stroke, pulmonary embolism) or chronic terminal illness were excluded. Institutional review boards of Ventura County Medical Center Oregon Health and Science University, Cedars-Sinai Health System, and all other relevant health systems and participating hospitals approved the study protocol
In the present study, we included all SCA cases of likely cardiac origin from Oregon SUDS and Ventura PRESTO studies that had PEA as the first recorded rhythm (i.e., presenting rhythm), had resuscitation attempted by EMS and had data on survival outcome. There were 25 (1.4%) PEA-SCA cases for whom data on survival status was not available, and were thus excluded. Cases with post-shock PEA were excluded. We ascertained all SCA cases between February 2002 and January 2018 in the Oregon SUDS study and between February 2015 and January 2022 in the Ventura PRESTO study. The rationale for the study subject selection is presented in Figure 1. Demographics and resuscitation-related characteristics (Utstein variables) were obtained from EMS reports, while data on prearrest clinical characteristics were obtained from lifetime clinical records. All study subjects had available data on demographics and resuscitation-related characteristics. Cases with available clinical records provided written consent, or, if the subject was deceased, consent was waived. PEA-SCAs that occurred in an ambulance (n=29), emergency department (ED, n=11), outpatient clinic (n=15), or dialysis (n=25) clinic were classified as PEA-SCAs in healthcare units.
Figure 1.
Study subject selection. PEA=pulseless electrical activity, SCA=sudden cardiac arrest, VF=ventricular fibrillation, VT=ventricular tachycardia.
Statistical analysis
All continuous variables are expressed as mean±standard deviation. Between-group differences were analyzed with the χ2 -test and Student’s t-test/analysis of variances (ANOVA)/Kruskal-Wallis/Mann-Whitney U test for categorical and continuous data, respectively. We considered continuous variables normally distributed after visual data inspection and skewness calculation (│skewness│< 1). For normally distributed continuous data (age, BMI), we used Student’s t-test/ANOVA for analyzing between-group differences while the Kruskal-Wallis/Mann-Whitney U test test was used to analyze between-group differences for continuous variables that were not normally distributed (EMS response time). If the omnibus p value was <0.05, post hoc analysis with χ2 -test or Bonferroni correction was applied. Logistic regression analysis with univariate and multivariable models was used to analyze odds ratios (OR) with 95% confidence intervals (CI) for resuscitation outcomes. We performed a univariate logistic regression model for each variable to determine the most important predictors of survival to hospital discharge. Subsequently, we performed a multivariable model in which we included age, sex, and all variables that had a p-value less than 0.10 in a univariate analysis. EMS response time was not included in the multivariable model since it was not applicable for EMS-witnessed PEA-SCAs. Statistical analyses were performed with the IBM Statistical Package for Social Studies (SPSS) version 24. All reported p values are two-sided and p values less than 0.05 were considered significant.
Results
In total, we identified 1,704 PEA-SCA cases, of which 173 (10.2%) were survivors and 1,531 (89.8%) were non-survivors. Ninety-one PEA-SCA survivors (53%) and 1,290 non-survivors (84%) had available prearrest clinical records. Of all cases, 70.7% occurred at home, while 13.5% occurred in care facilities, 11.3% in public locations, and 4.5% in healthcare units. Survival to hospital discharge rates was significantly higher if PEA-SCA occurred in a public location (18.1%) or healthcare units (16.9%) than if PEA-SCA occurred at home (9.3%) or in care facilities (5.7%; p<0.001).
Demographics and clinical characteristics between survivors and non-survivors
Those who survived were significantly younger compared to non-survivors (64.4±17.2 vs. 71.2±15.4; p<0.001, Supplemental Figure). There was no significant difference in BMI (29.6±8.7 kg/m2 vs. 30.1±9.8 kg/m2; p=0.58), race/ethnicity distribution (p=0.19), or in the proportion of female sex (43.4% vs. 37.1%; p=0.12) between survivors and non-survivors, respectively.
As expected, the proportion of witnessed arrests was higher among survivors (79.2% vs. 66.1%; p<0.001) but there was no difference in the rate of bystander CPR (34.1% vs. 34.0%; p=0.97) between survivors and non-survivors. The prevalence of previously diagnosed COPD/asthma was higher among PEA-SCA survivors than in non-survivors (35.2% vs. 25.0%; p=0.04). Demographics, resuscitation-related characteristics, and prearrest clinical comorbidities among survivors and non-survivors are presented in Supplemental Table 1, Figure 2 and Figure 3.
Figure 2.
Distribution of comorbidity burden shown as the number of conditions in proportions of patients, e.g., 14.8% of survivors had no comorbidities and 1.1% had 7 comorbidities, while 22.7% of non-survivors had no comorbidities and 1.1% had 7 comorbidities. P value for difference 0.16.
Figure 3.
Prearrest clinical characteristics between PEA survivors and non-survivors. *p=0.04. CABG=coronary artery bypass graft surgery, CAD=coronary artery disease, CKD=chronic kidney disease, CPR=cardiopulmonary resuscitation, COPD=chronic obstructive pulmonary disease, HF=heart failure, ICD=implantable cardioverter-defibrillator, MI=myocardial infarction, PCI=percutaneous coronary intervention.
Characteristics according to location of PEA-SCA
Given the significant differences in survival rates and clinical profiles according to PEA-SCA location, we have compared case characteristics between different PEA-SCA locations. The mean age was the highest among those who had PEA-SCA in care facilities (75.7±14.4), while those who had PEA-SCA in a public location were the youngest (64.2±16.1; p<0.001). Similarly, the prevalence of female sex was the highest among those who had PEA-SCA in care facilities (48.9%) and lowest among those who had PEA-SCA in a public location (20.7%; p<0.001). The rate of witnessed arrest was highest in PEA-SCAs that occurred in healthcare units (96.2%), while PEA-SCAs that occurred in care facilities had the lowest proportion of witnessed arrests (53.7%; p<0.001). The rate of bystander CPR was highest in PEA-SCAs occurring in care facilities (55.5%) and lowest in PEA-SCAs at home (28.9%; p<0.001). The burden of prearrest comorbidities was highest among those whose PEA-SCA occurred in healthcare units. Particularly, the prevalence of heart failure (49.2%), coronary artery disease (44.6%), diabetes (52.3%), and chronic kidney disease (55.4%) were highest among PEA-SCAs that occurred in healthcare units. Demographics and clinical characteristics according to cardiac arrest location are presented in Table 1 and Supplemental Table 2.
Table 1.
Demographics and resuscitation-related characteristics according to cardiac arrest location.
| Overall (n=1,702)* | Home (n=1,203) | Healthcare unit (n=77) | Public location (n=193) | Care facility (n=229) | P value | |
|---|---|---|---|---|---|---|
| Age | 70.5±15.8 | 70.7±15.7 | 68.3±14.4 | 64.2±16.1 | 75.7±14.4 | <0.001bcef |
| Female sex | 641/1,702 (37.7%) | 464/1,203 (38.6%) | 25/77 (32.5%) | 40/193 (20.7%) | 112/229 (48.9%) | <0.001bcf |
| BMI, kg/m² | 30.1±9.7 | 30.4±10.1 | 31.3±8.1 | 29.8±7.7 | 28.2±9.3 | 0.06 |
| Race/ethnicity | 0.06 | |||||
| White | 1,215/1,646 (73.8%) | 837/1,166 (71.8%) | 52/75 (69.3%) | 149/183 (81.4%) | 177/222 (79.7%) | |
| Hispanic | 204/1,646 (12.4%) | 165/1,166 (14.2%) | 11/75 (14.7%) | 10/183 (5.5%) | 18/222 (8.1%) | |
| Black | 128/1,646 (7.8%) | 90/1,166 (7.7%) | 6/75 (8.0%) | 14/183 (7.7%) | 18/222 (8.1%) | |
| Asian | 79/1,646 (4.8%) | 59/1,166 (5.1%) | 6/75 (8.0%) | 7/183 (3.8%) | 7/222 (3.2%) | |
| Other | 20/1,646 (1.2%) | 15/1,166 (1.3%) | 0/75 (0%) | 3/183 (1.6%) | 2/222 (0.9%) | |
| Witness status | <0.001abcdef | |||||
| Unwitnessed | 554/1,698 (32.6%) | 394/1,199 (32.9%) | 3/77 (3.9%) | 51/193 (26.4%) | 106/229 (46.3%) | |
| Bystander witnessed | 833/1,698 (49.1%) | 587/1,199 (49.0%) | 37/77 (48.1%) | 115/193 (59.6%) | 94/229 (41.0%) | |
| EMS witnessed | 311/1,698 (18.3%) | 218/1,199 (18.2%) | 37/77 (48.1%) | 27/193 (14.0%) | 29/229 (12.7%) | |
| Bystander CPR | 588/1,191 (34.2%) | 351/1,214 (28.9%) | 32/80 (40.0%) | 78/196 (39.8%) | 127/229 (55.5%) | <0.001bcf |
| EMS response time** | 6.7±3.0 | 6.8±3.1 | 6.3±2.7 | 6.8±2.8 | 6.3±2.4 | 0.20 |
BMI=body mass index, CPR=cardiopulmonary resuscitation, EMS=emergency medical services. If the omnibus p value was <0.05, post hoc analysis with χ2 -test or Bonferroni correction was applied. Only statistically significant pairwise results are marked in the footnotes.
Data on SCA location missing from 2 cases.
EMS-witnessed cases not included.
Comparison between home and healthcare unit groups.
Comparison between home and public location groups.
Comparison between home and care facility groups.
Comparison between healthcare unit and public location groups.
Comparison between healthcare unit and care facility groups.
Comparison between public location and care facility groups.
Multivariable model for survival
In the univariate models, the following variables were associated with survival from the PEA-SCA event (p-value < 0.10): age, witnessed arrest, PEA-SCA location, prior heart failure, prior COPD/asthma, and prior sleep apnea. These variables were included in the multivariable model, in which age (OR 0.99, 95% CI 0.97–0.99; p=0.04), EMS witnessed arrest (OR 2.12, 95% CI 1.09–4.13; p=0.03), PEA-SCA in a public location (OR 4.14, 95% CI 2.35–7.31; p<0.001, in comparison to PEA-SCA at home), and prior COPD/asthma (OR 1.68, 95% CI 1.03–2.74; p=0.04) were associated with survival to hospital discharge (Table 2).
Table 2.
Univariate and multivariable models for factors associated with survival to hospital discharge.
| Univariate model | Multivariable model | |||
|---|---|---|---|---|
| OR (95% CI) | P value | OR (95% CI) | P value | |
| Age | 0.98 (0.97–0.99) | <0.001 | 0.99 (0.97–0.99) | 0.04 |
| Female sex | 1.30 (0.94–1.78) | 0.11 | 1.34 (0.84–2.13) | 0.22 |
| Witness status | ||||
| Unwitnessed | Ref | Ref | Ref | Ref |
| Bystander witnessed arrest | 1.90 (1.09–3.29) | 0.02 | 1.48 (0.83–2.63) | 0.18 |
| EMS witnessed arrest | 2.42 (1.28–4.58) | 0.01 | 2.12 (1.09–4.13) | 0.03 |
| Location | ||||
| Home | Ref | Ref | Ref | Ref |
| Healthcare unit | 1.98 (1.06–3.71) | 0.03 | 2.01 (0.88–4.60) | 0.10 |
| Public | 2.16 (1.43–3.27) | <0.001 | 4.14 (2.35–7.31) | <0.001 |
| Care facility | 0.59 (0.32–1.06) | 0.08 | 0.94 (0.44–1.97) | 0.86 |
| Heart failure | 1.56 (1.02–2.40) | 0.04 | 1.48 (0.91–2.40) | 0.11 |
| COPD/asthma | 1.63 (1.03–2.57) | 0.04 | 1.68 (1.03–2.74) | 0.04 |
| Sleep apnea | 1.83 (1.00–3.33) | 0.05 | 1.28 (0.67–2.45) | 0.45 |
CAD=coronary artery disease, COPD=chronic obstructive pulmonary disease, EMS=emergency medical services, PCI=percutaneous coronary intervention.
We were able to collect data on prehospital airway management from 739 PEA-SCA cases with available prearrest medical records. Of these cases, 283 (38%) had advanced airways successfully placed in the field, with no statistically significant difference between cases with or without COPD/asthma (40% vs. 38%, respectively; p=0.89).
Survival according to witness status and EMS response time
Given that survival to hospital discharge is highly dependent on the witness status and time to the initiation of appropriate treatment, we analyzed PEA-SCA survival rates according to bystander witness status, bystander CPR, and EMS response time to find subgroups of PEA-SCA cases that are unlikely to benefit from resuscitation efforts. Among witnessed PEA-SCA cases, survival rates remained relatively high regardless of the EMS response time. However, among unwitnessed cases, the survival rate was dependent on EMS response time, and none of the unwitnessed PEA-SCA cases survived if the EMS response time exceeded 10 minutes (Figure 4).
Figure 4.
Survival to hospital discharge rate according to bystander witness status, bystander CPR and EMS response time in PEA-SCA cases not witnessed by EMS. EMS=emergency medical services, PEA=pulseless electrical activity, SCA=sudden cardiac arrest.
Discussion
In this study, we aimed to identify key predictors of survival from PEA-SCA from two prospective, community-based studies of out-of-hospital SCAs. At least 10% of PEA-SCA cases survived to hospital discharge. Cases that were witnessed or occurred in a public location or healthcare unit had the highest chance of survival. Young age and pre-existing COPD/asthma were independent predictors of survival. Among witnessed PEA-SCA cases, the survival rate remained 10% even if the EMS response time was >10 minutes, suggesting that resuscitation efforts should not be withheld in such cases.
Hypoxia is a common precipitating factor for PEA(21), but recognition of hypoxia as a trigger is reliable only in the <20% of cases witnessed by EMS. At least 80% of out-of-hospital SCAs are unwitnessed by EMS with no availability of prearrest physiologic measurements(22). Unlike most reports of out-of-hospital SCA, our study design enabled the evaluation of the prearrest clinical profile, which showed that pre-existing COPD/asthma was relatively common in PEA-SCA and also a significant predictor of survival. This may suggest that cases triggered by hypoxia represent a “sweet spot” for survival from PEA-SCA cases since they generally respond well to airway management, and consequently associate with a better prognosis. However, we cannot be sure that PEA was precipitated by hypoxia in these cases, and further studies are needed to validate this finding.
We report that if the PEA-SCA event was witnessed and EMS response time was >10 minutes, the survival rate was still 10%, suggesting that resuscitation efforts should not be withheld in such cases. PEA-SCA is a heterogeneous condition, and some cases may have a trigger that has the potential to respond well to an appropriate therapy even after a 10-minute delay (e.g., acute MI or hypoxia with significant myocardial contractility reserve). Continuing vs. withholding/terminating resuscitation remains an area of active debate for non-shockable rhythms with a larger focus on asystole. Withholding resuscitation can be recommended in unwitnessed asystole cases (excluding hypothermia and near-drowning) and in persistent asystole after 20 min of advanced life support (5, 6, 32). Previous studies on PEA-SCAs have suggested that unwitnessed cases >80 years and cases with EMS response time over 15 min have no chance of survival (27, 28). Our results are somewhat in contrast to these findings since 8% of unwitnessed cases over 80 years survived and 1/21 (5%) of cases with EMS response time >15 minutes survived to hospital discharge (bystander witnessed case). We also found that if PEA-SCA was unwitnessed and EMS response time was more than 10 minutes, the survival rate was zero. Given that a prolonged delay in life support initiation predisposes to anoxic brain injury, survivors with longer EMS response times may, however, have more severe neurologic complications and poorer neurologic recovery after hospital discharge.
In addition to hypoxia, a significant proportion of PEA-SCAs have residual myocardial contractile function which is an important predictor of survival (23, 24). In the present study, pre-existing heart failure was also common and associated with a non-significant trend toward better survival. Heart failure-related PEA-SCA cases may represent acute pump failure with residual myocardial contractility and profound hypotension.(25) This is a setting in which rapid initiation of advanced life support with early adrenaline administration, airway management, and cause-specific treatment could have beneficial effects on survival (26). However, in this study we did not have data on EMS measured ultrasound findings to support this hypothesis.
Young age was also an independent predictor of survival to hospital discharge. This is somewhat consistent with our previous study on PEA-SCA survivors, in which we found that young survivors have an excellent long-term prognosis(16). It appears that young patients are not only more likely to survive PEA-SCA but also have a more favorable prognosis after hospital discharge than older individuals.
Interestingly, bystander CPR was not associated with survival. This finding is in parallel with recent studies which have also reported that bystander CPR does not associate with survival in PEA-SCA (9, 27). While the exact reasons are not fully clear, bystander CPR may have variable quality in the community, or only a moderate effect on survival, which may attenuate the association in our study. In contrast, a slightly older study twenty years ago reported that bystander CPR was associated with survival in PEA-SCA, but the proportion of cases receiving bystander CPR was much lower than in our study (9% vs. 34.2%) (28). Thus, it raises speculation whether only a small proportion of PEA-SCAs are likely to benefit from bystander CPR.
In contrast to PEA-SCAs in public locations, PEA-SCAs that occurred in healthcare units were somewhat older and had a significantly higher prevalence of previously diagnosed comorbidities. A possible explanation may be related to warning symptoms, higher SCA awareness, and seek for immediate medical care. Although SCA is usually considered a sudden and unexpected event, several studies have found that more than half of the cases are preceded by warning symptoms, mostly chest pain and dyspnea (29–31), and contacting EMS before the impending SCA is crucial for survival (29). Data from Oregon SUDS demonstrated that those who contacted EMS before the arrest were older and more likely to have previously been diagnosed with cardiac disease(29), suggesting that pre-existing cardiac disease may associate with higher SCA awareness. Our findings are also in parallel with previous studies which have found that EMS-witnessed SCAs associate with a high burden of prior cardiovascular or respiratory diseases(22). Given that only 4.5% of the PEA-SCA cases in our study occurred in healthcare units, there is significant room for improvement in the near-term prevention of PEA-SCA-related mortality.
Limitations
Our study has some limitations that need to be addressed. Firstly, we had prearrest clinical records available only on 81% of all PEA-SCA cases and 53% of survivors, which is a potential source of selection bias. We were not able to include survivors in the analysis of prearrest comorbidities if we could not contact them due to a combination of factors (e.g., moving to a different address or phone number, or poor neurological survival) (82%, n=67), if the patient refused consent for access to their medical records (17%, n=14), or if medical records could not be located (1%, n=1). For non-survivors, consent was waived, and hence the proportion of available medical records was significantly higher. The remaining 16% missingness in non-survivors may be attributable to a combination of factors including cardiac arrest as the first manifestation of any illness or if we were unsuccessful in obtaining medical records. However, given our study design, the latter possibility is small. Secondly, we cannot be fully sure that PEA was the actual primary rhythm in all cases and not a result of spontaneous rhythm transition before the rhythm recording. Thirdly, we had no data on patient/witness response time (e.g., time from collapse to call), and hence we were unable to analyze the effect of patient/witness response on the survival rate. In addition, we have collected SCA cases over 20 years, during which there may have been changes in patient characteristics. We had no data on time to first epinephrine administration or post-arrest therapeutic temperature management, which may have affected survival rates. Our study population is drawn from two U.S. communities, and future studies are needed to address the generalizability of our results. Finally, we had no data on the overall performance category to analyze the proportion of PEA-SCA survivors with good functional recovery or disabilities. Further studies are needed to validate our findings regarding survival and neurologic recovery especially in cases with prolonged EMS response time.
Conclusions
Key determinants for survival from PEA-SCA were young age, witnessed status, public location and pre-existing COPD/asthma. Even with delayed EMS response, survival outcomes in witnessed PEA cases were better than expected, with implications for the ongoing debate regarding the optimal approach to resuscitation of SCA with non-shockable rhythms.
Supplementary Material
Acknowledgments
This work is funded, in part, by the National Institutes of Health, National Heart Lung and Blood Institute Grants R01HL145675 and R01HL147358 to SSC. SSC holds the Pauline and Harold Price Chair in Cardiac Electrophysiology at Cedars-Sinai. LH is a postdoctoral fellow visiting from the Research Unit of Internal Medicine, Medical Research Center Oulu, University of Oulu and Oulu University Hospital, Oulu, Finland, and is funded by Sigrid Juselius Foundation, The Finnish Cultural Foundation, Instrumentarium Science Foundation, Orion Research Foundation, and Paavo Nurmi Foundation. The funding sources had no involvement in the preparation of this work or the decision to submit it for publication.
Footnotes
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Conflicts of interest
No conflicts of interest
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Declarations of interest: none
CRediT authorship contribution statement
Lauri Holmstrom: Formal analysis, Writing – original draft. Harpriya Chugh: Data Curation, Investigation, Writing – review & editing. Audrey Uy-Evanado: Investigation, Writing – review & editing. Angelo Salvucci: Investigation, Writing – review & editing. Jonathan Jui: Investigation, Writing – review & editing. Kyndaron Reinier: Investigation, Writing – review & editing. Sumeet S. Chugh: Conceptualization, Investigation, Methodology, Resources, Supervision, Project administration, Writing – original draft, Writing – review & editing.
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