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The Danish Drowning Formula (DDF) was designed to search the unstructured text fields in the Danish nationwide Prehospital Electronic Medical Record on unrestricted terms with comprehensive search criteria to identify all potential water-related incidents and achieve a high sensitivity. This was important as drowning is a rare occurrence, but it resulted in a low Positive Predictive Value for detecting drowning incidents specifically. This study aims to augment the positive predictive value of the DDF and reduce the temporal demands associated with manual validation.
The DDF was published in 2023. It is a text-search algorithm designed to search the unstructured text fields in databases containing electronic medical records to identify all potential water-related incidents. The DDF consists of numerous trigger words related to submersion injury (e.g., "drukn"/ drown, "vand"/water, "hav"/ocean, and "baÌŠd"/ boat).
An ongoing study showed impressive performance metrics of the DDF as a drowning identification tool when applied to the Danish PEMR on unrestricted terms. However, the PPV was low for detecting drowning incidents specifically. This study aims to augment the DDF's positive predictive value and reduce the temporal demands associated with manual validation.
Data are extracted from the Danish nationwide Prehospital Electronic Medical Record using the DDF and manually validated before entered into the Danish Prehospital Drowning Data (DPDD).
Data from the DPDD from 2016-2021 will be split into 80% (training data) and 20% (test data) and used to train the machine learning.
Data from the DPDD from 2022-2023 will be used as validation data to calculate the performance metrics for the machine learning.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Fatal drowning | Drowning incidents where the patient died within 30 days after the incident as a consequence of the submersion injury |
| |
| Non-fatal drowning | Drowning incidents where the patient survived to 30 days |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Drowning incident | Other | Drowning was defined by the WHO in 2002 as "the process of experiencing respiratory impairment from submersion or immersion in liquid". |
|
| Measure | Description | Time Frame |
|---|---|---|
| Sensitivity of the machine learning algorithm as a drowning identification tool | Sensitivity [TP / (TP+FN)] will be calculated to show the performance of the machine learning as a drowning identification tool. | The sensitivity of the trained machine learning will be calculated based on data from 2022 and 2023. |
| Specificity of the machine learning algorithm as a drowning identification tool | Specificity [TN / (FP+TN)] will be calculated to show the performance of the machine learning as a drowning identification tool. | The specificity of the trained machine learning will be calculated based on data from 2022 and 2023. |
| PPV of the machine learning algorithm | PPV [TP / (TP+FP)] will be calculated to show the machine learning test result. | The PPV of the trained machine learning will be calculated based on data from 2022 and 2023. |
| NPV of the machine learning algorithm | NPV [TN / (FN+TN)] will be calculated to show the machine learning test result. | The NPV of the trained machine learning will be calculated based on data from 2022 and 2023. |
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Inclusion Criteria:
Exclusion Criteria:
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All fatal and non-fatal drowning patients in Denmark treated by the Emergency Medical Services (EMS) between 2016 and 2023.
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| Name | Affiliation | Role |
|---|---|---|
| Helle Collatz Christensen, Ass. Prof. | Prehospital Center, Region Zealand | Study Director |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Prehospital Center | Næstved | Region Sjælland | 4700 | Denmark |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 37619443 | Background | Breindahl N, Wolthers SA, Jensen TW, Holgersen MG, Blomberg SNF, Steinmetz J, Christensen HC; Danish Cardiac Arrest Group. Danish Drowning Formula for identification of out-of-hospital cardiac arrest from drowning. Am J Emerg Med. 2023 Nov;73:55-62. doi: 10.1016/j.ajem.2023.08.024. Epub 2023 Aug 15. | |
| 38448994 | Background |
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The data are intended for use nationally and internationally by researchers to reduce the incidence, mortality, and morbidity of drowning. The data are available upon reasonable request from researchers after application to the corresponding author, provided the necessary approvals are obtained from the relevant authorities.
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| Breindahl N, Wolthers SA, Moller TP, Blomberg SNF, Steinmetz J, Christensen HC; Danish Drowning Validation Group. Characteristics and critical care interventions in drowning patients treated by the Danish Air Ambulance from 2016 to 2021: a nationwide registry-based study with 30-day follow-up. Scand J Trauma Resusc Emerg Med. 2024 Mar 6;32(1):17. doi: 10.1186/s13049-024-01189-y. |
| 39885431 | Derived | Breindahl N, Bitzer K, Sorensen OB, Wildenschild A, Wolthers SA, Lindskou T, Steinmetz J, Blomberg SNF, Christensen HC; Danish Drowning Validation Group. The Danish Drowning Cohort: Utstein-style data from fatal and non-fatal drowning incidents in Denmark. BMC Med Res Methodol. 2025 Jan 30;25(1):28. doi: 10.1186/s12874-025-02483-8. |
| ID | Term |
|---|---|
| D004332 | Drowning |
| D015701 | Near Drowning |
| D001237 | Asphyxia |
| ID | Term |
|---|---|
| D003643 | Death |
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |
| D014947 | Wounds and Injuries |
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