Prediction model for future OHCAs based on geospatial and demographic data: An observational study
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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Prediction model for future OHCAs based on geospatial and demographic data : An observational study. / Bundgaard Ringgren, Kristian; Ung, Vilde; Gerds, Thomas Alexander; Kragholm, Kristian Hay; Ascanius Jacobsen, Peter; Lyng Lindgren, Filip; Grabmayr, Anne Juul; Christensen, Helle Collatz; Mills, Elisabeth Helen Anna; Kollander Jakobsen, Louise; Yonis, Harman; Hansen, Carolina Malta; Folke, Fredrik; Lippert, Freddy; Torp-Pedersen, Christian.
I: Medicine (United States), Bind 103, Nr. 19, E38070, 2024.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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TY - JOUR
T1 - Prediction model for future OHCAs based on geospatial and demographic data
T2 - An observational study
AU - Bundgaard Ringgren, Kristian
AU - Ung, Vilde
AU - Gerds, Thomas Alexander
AU - Kragholm, Kristian Hay
AU - Ascanius Jacobsen, Peter
AU - Lyng Lindgren, Filip
AU - Grabmayr, Anne Juul
AU - Christensen, Helle Collatz
AU - Mills, Elisabeth Helen Anna
AU - Kollander Jakobsen, Louise
AU - Yonis, Harman
AU - Hansen, Carolina Malta
AU - Folke, Fredrik
AU - Lippert, Freddy
AU - Torp-Pedersen, Christian
N1 - Publisher Copyright: © 2024 Lippincott Williams and Wilkins. All rights reserved.
PY - 2024
Y1 - 2024
N2 - This study used demographic data in a novel prediction model to identify areas with high risk of out-of-hospital cardiac arrest (OHCA) in order to target prehospital preparedness. We combined data from the nationwide Danish Cardiac Arrest Registry with geographical- and demographic data on a hectare level. Hectares were classified in a hierarchy according to characteristics and pooled to square kilometers (km2). Historical OHCA incidence of each hectare group was supplemented with a predicted annual risk of at least 1 OHCA to ensure future applicability. We recorded 19,090 valid OHCAs during 2016 to 2019. The mean annual OHCA rate was highest in residential areas with no point of public interest and 100 to 1000 residents per hectare (9.7/year/km2) followed by pedestrian streets with multiple shops (5.8/year/km2), areas with no point of public interest and 50 to 100 residents (5.5/year/km2), and malls with a mean annual incidence per km2 of 4.6. Other high incidence areas were public transport stations, schools and areas without a point of public interest and 10 to 50 residents. These areas combined constitute 1496 km2 annually corresponding to 3.4% of the total area of Denmark and account for 65% of the OHCA incidence. Our prediction model confirms these areas to be of high risk and outperforms simple previous incidence in identifying future risk-sites. Two thirds of out-of-hospital cardiac arrests were identified in only 3.4% of the area of Denmark. This area was easily identified as having multiple residents or having airports, malls, pedestrian shopping streets or schools. This result has important implications for targeted intervention such as automatic defibrillators available to the public. Further, demographic information should be considered when implementing such interventions.
AB - This study used demographic data in a novel prediction model to identify areas with high risk of out-of-hospital cardiac arrest (OHCA) in order to target prehospital preparedness. We combined data from the nationwide Danish Cardiac Arrest Registry with geographical- and demographic data on a hectare level. Hectares were classified in a hierarchy according to characteristics and pooled to square kilometers (km2). Historical OHCA incidence of each hectare group was supplemented with a predicted annual risk of at least 1 OHCA to ensure future applicability. We recorded 19,090 valid OHCAs during 2016 to 2019. The mean annual OHCA rate was highest in residential areas with no point of public interest and 100 to 1000 residents per hectare (9.7/year/km2) followed by pedestrian streets with multiple shops (5.8/year/km2), areas with no point of public interest and 50 to 100 residents (5.5/year/km2), and malls with a mean annual incidence per km2 of 4.6. Other high incidence areas were public transport stations, schools and areas without a point of public interest and 10 to 50 residents. These areas combined constitute 1496 km2 annually corresponding to 3.4% of the total area of Denmark and account for 65% of the OHCA incidence. Our prediction model confirms these areas to be of high risk and outperforms simple previous incidence in identifying future risk-sites. Two thirds of out-of-hospital cardiac arrests were identified in only 3.4% of the area of Denmark. This area was easily identified as having multiple residents or having airports, malls, pedestrian shopping streets or schools. This result has important implications for targeted intervention such as automatic defibrillators available to the public. Further, demographic information should be considered when implementing such interventions.
U2 - 10.1097/MD.0000000000038070
DO - 10.1097/MD.0000000000038070
M3 - Journal article
C2 - 38728490
AN - SCOPUS:85192948120
VL - 103
JO - Medicine (Baltimore)
JF - Medicine (Baltimore)
SN - 0025-7974
IS - 19
M1 - E38070
ER -
ID: 392582536