Study Results
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Basic Information
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UNKNOWN
31200 participants
OBSERVATIONAL
2022-06-01
2023-06-01
Brief Summary
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Machine Learning Assisted Recognition of Out-of-Hospital Cardiac Arrest During Emergency Calls.
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Detailed Description
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With aid of machine learning, the hypothesis is that advances text searches may lead to improvement of quality of data from the Danish registry of OHCA. With this improvement this project might contribute to the handling and strategies concerning defined subgroups within OHCA.
Furthermore, we speculate that this novel data from the EMS medical reports provide new and central data reversible on causes, which presumably are linked to enhanced survival of OHCA of non-cardiac origin. Thus, this study aims to:
* Investigate descriptives of traumatic out-of-hospital cardiac arrest, drug overdose, electrocution and external asphyxia leading to cardiac arrest
* Assess outcomes of cardiac arrests of non-cardiac origin
* Evaluate inter- and intrasystem comparisons
Data on OHCA's with attempted resuscitation in Denmark have been collected in the electronic based Danish Medical Service reporting system since 2016. The registry covers detailed data including the EMS report. The data consists of executive entries and advanced text searches of prehospital charts in conjunction, augmenting the identification and collecting all OHCA's in Denmark. All cases have been through an elaborate validation process of which all identified events were read through manually. This was conducted by an external verification team to corroborate high quality of data throughout the approximately 5400 cases of OHCA in Denmark annually. Within this practice of verification, supplementary sources of data have been linked to each individual case of OHCA; information of certain interest was survival, localization, initiation of bystander CPR and actions from EMS personnel.
Identification of subgroups
Within this diverse entity of OHCA's further investigation of subgroups are required. Through advanced text searches using a bag-of-words model within the prehospital medical record, cases of interest among the predefined subgroups will be identified; thus, is text-string searches developed for every subgroup. These predefined subgroups will be defined as trauma, drowning, electrocution, drug overdose and asphyxia (external) according to the Utstein template. The identified cases will be coupled to the national registry after external manual validation.
Variables included
* Age: Age will be defined as the subject age at the time of the event.
* Sex: Sex will be stated as either male, female or undetermined derived from personal identification numbers. Gender will be characterized based on EMS-charts, in those cases without an identification number.
* Initial rhythm: The initial rhythm will be defined as the first rhythm observed by EMS personnel, and categorized as either shockable, non-shockable (asystole), non-shockable (other) or undetermined.
* Etiology of cardiac arrest: Presumed causes will be stated as either presumed cardiac, other medical cause, trauma, drug overdose, drowning, electrocution or asphyxia (external).
* Location of Incidence: Location will be characterized as either residential area, outdoors and nature, private home or other.
* Observation of occurrence: Cardiac arrests will be defined as either unwitnessed, bystander witnessed or EMS-witnessed.
* Cardio-pulmonary-resuscitation: CPR will include bystander-initiated CPR and EMS treatment with CPR.
* Defibrillation and use of automatic external defibrillators: Defibrillation will include defibrillation by bystanders and/or EMS personnel. Use of AED's includes using the device also in the case it did not deliver shocks.
* EMS-response time: This will be defined as the time between a dispatcher receiving the emergency call and the arrival of the first EMS-personnel.
* Hospitalization: Hospitalization will be considered as either; transported to hospital or declared dead by EMS-personnel.
* Return-of-spontaneous-circulation (ROSC): ROSC will be classified as the achievement of ROSC anytime between recognition of the event and termination (defined as either hospital admission or declaration of death by EMS-personnel).
* State at hospital admission: State of the case upon arrival at the hospital will be defined as either ROSC or ongoing CPR.
* Survival: Survival will be defined as ROSC at the time of hospital admission, additionally 30-day survival will be included, this derived from data from the National Patient Registry.
* Airway management: This includes the airway manoeuvres performed on each case. It is defined by listing the use of airway adjuncts such as nasopharyngeal airway, oropharyngeal airway as well as endo-tracheal intubation, supraglottic airway device and isolated bag-valve-mask ventilation.
* Use of Medication: This includes a dichotomous (yes/no) variable based upon the potential administration of medication (ie epinephrine) for each case.
Analysis and Data Presentation
All data will be pseudo-anonymized, and all analyses will be accomplished on an aggregated nationwide level. Data is collected using the STROBE (STrengthening the Reporting of OBservational studies in Epidemiology) statement. The objective of this project is to clarify etiology, descriptive data and prehospital interventions of different subgroups of OHCA's. Descriptive statistics includes the above-mentioned variables labelled with absolute numbers and percentages. Comparative analyses will be carried out using non-parametric testing to examine subgroups. Forward logistic regression analysis will be performed for multivariate analysis. Within this multivariate logistic regression analysis both known and unknown variables will be processed. Odds ratio for survival will be calculated stratified by etiology, localization, bystander and EMS-actions.
Risk Management Strategy and Ethical Considerations Since it is registry-based research, there is no patient contact and of such no harm possible or further ethical considerations of concern. GDPR will be followed according to danish law and the studies will be registered at the Danish Data Protection Agency, capital region of Denmark. According to Danish legislation, register-based research does not require ethical committee approval nor patient consent.
Perspectives
This project provides novel information regarding these subgroups of OHCA; The way of using artificial intelligence within text mining allows high quality use of data in order to strengthen the results. Thus, the descriptive statistics provides relevant data based on a reviewed, high-quality database. Furthermore, throughout analyses, a better understanding of the preceding circumstances, etiology and prehospital assessment might contribute to improve handling these types of arrests. This, eventually through use of campaigns, education and training targeted laypersons and healthcare personnel, respectly.
Publication The results are targeted for publication in an international peer reviewed journal. Signe Amalie Wolthers is primary investigator of this project and will be listed as first author. Participation as coauthors will be decided according to the Vancouver criteria or acknowledged for providing access to data. All Danish regional EMS regions will receive this manuscript prior to publication for eventual comments.
Conditions
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Study Design
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COHORT
RETROSPECTIVE
Study Groups
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All cause OHCA
No interventions assigned to this group
OHCA of non-cardiac origin
No interventions assigned to this group
Eligibility Criteria
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Inclusion Criteria
Exclusion Criteria
ALL
No
Sponsors
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Prehospital Center, Region Zealand
OTHER
Responsible Party
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Signe Amalie Wolthers
MD, principal investigator
Locations
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Prehospital Center
Næstved, , Denmark
Countries
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References
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Cummins RO, Chamberlain DA, Abramson NS, Allen M, Baskett PJ, Becker L, Bossaert L, Delooz HH, Dick WF, Eisenberg MS, et al. Recommended guidelines for uniform reporting of data from out-of-hospital cardiac arrest: the Utstein Style. A statement for health professionals from a task force of the American Heart Association, the European Resuscitation Council, the Heart and Stroke Foundation of Canada, and the Australian Resuscitation Council. Circulation. 1991 Aug;84(2):960-75. doi: 10.1161/01.cir.84.2.960. No abstract available.
Lindskou TA, Mikkelsen S, Christensen EF, Hansen PA, Jorgensen G, Hendriksen OM, Kirkegaard H, Berlac PA, Sovso MB. The Danish prehospital emergency healthcare system and research possibilities. Scand J Trauma Resusc Emerg Med. 2019 Nov 4;27(1):100. doi: 10.1186/s13049-019-0676-5.
Claesson A, Djarv T, Nordberg P, Ringh M, Hollenberg J, Axelsson C, Ravn-Fischer A, Stromsoe A. Medical versus non medical etiology in out-of-hospital cardiac arrest-Changes in outcome in relation to the revised Utstein template. Resuscitation. 2017 Jan;110:48-55. doi: 10.1016/j.resuscitation.2016.10.019. Epub 2016 Nov 5.
Christensen DM, Rajan S, Kragholm K, Sondergaard KB, Hansen OM, Gerds TA, Torp-Pedersen C, Gislason GH, Lippert FK, Barcella CA. Bystander cardiopulmonary resuscitation and survival in patients with out-of-hospital cardiac arrest of non-cardiac origin. Resuscitation. 2019 Jul;140:98-105. doi: 10.1016/j.resuscitation.2019.05.014. Epub 2019 May 23.
Lott C, Truhlar A, Alfonzo A, Barelli A, Gonzalez-Salvado V, Hinkelbein J, Nolan JP, Paal P, Perkins GD, Thies KC, Yeung J, Zideman DA, Soar J; ERC Special Circumstances Writing Group Collaborators. European Resuscitation Council Guidelines 2021: Cardiac arrest in special circumstances. Resuscitation. 2021 Apr;161:152-219. doi: 10.1016/j.resuscitation.2021.02.011. Epub 2021 Mar 24.
Kleber C, Giesecke MT, Lindner T, Haas NP, Buschmann CT. Requirement for a structured algorithm in cardiac arrest following major trauma: epidemiology, management errors, and preventability of traumatic deaths in Berlin. Resuscitation. 2014 Mar;85(3):405-10. doi: 10.1016/j.resuscitation.2013.11.009. Epub 2013 Nov 25.
Hess EP, Campbell RL, White RD. Epidemiology, trends, and outcome of out-of-hospital cardiac arrest of non-cardiac origin. Resuscitation. 2007 Feb;72(2):200-6. doi: 10.1016/j.resuscitation.2006.06.040. Epub 2006 Nov 22.
Other Identifiers
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AI_CA_2022
Identifier Type: -
Identifier Source: org_study_id
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