The following is a summary of “Danish Drowning Formula for identification of out-of-hospital cardiac arrest from drowning,” published in the November 2023 issue of Emergency Medicine by Breindahl, et al.

Accurate drowning statistics are crucial for effective preventive measures and treatment improvements. Current methods of reporting drowning incidents may lead to significant underreporting. For a study, researchers sought to assess the 30-day survival of out-of-hospital cardiac arrest (OHCA) patients identified in the Danish Cardiac Arrest Registry (DCAR) using the Danish Drowning Formula.

The nationwide cohort study utilized the Danish Drowning Formula, a text-search algorithm developed for this purpose, to identify drowning-related OHCA cases in the DCAR between January 1, 2016, and December 31, 2021. The formula was constructed based on trigger words identified from prehospital medical records of validated drowning cases. The primary outcome was the 30-day survival from OHCA. Data were analyzed using multiple logistic regression.

Out of 29,882 OHCA cases, 374 (1%) were identified as drowning-related in the DCAR. Drowning-related OHCAs were more likely to occur in public locations (87% vs. 25%, P < 0.001) and were often witnessed by bystanders (80% vs. 55%, P < 0.001). Both 30-day and 1-year survival rates for drowning-related OHCA were significantly higher compared to OHCA from other causes (33% vs. 14% and 32% vs. 13%, respectively, P < 0.001). The adjusted odds ratio for 30-day survival was 2.3 [1.7–3.2], P < 0.001, favoring drowning-related OHCA. Notably, drowning-related OHCA at swimming pools showed increased 30-day survival compared to public location OHCA from other causes, with an odds ratio of 11.6 [6.0–22.6], P < 0.001.

The study revealed higher 30-day survival rates for drowning-related OHCA compared to OHCA from other causes. The proposed Danish Drowning Formula, a text-search algorithm, offers a low-resource solution for identifying drowning incidents and may contribute to more accurate drowning statistics in the future.

Source: sciencedirect.com/science/article/pii/S0735675723004448