Cargando…
Clinical Predictors of Mortality in Prehospital Distress Calls by Emergency Medical Service Subscribers
(1) Introduction: Most studies rely on in-hospital data to predict cardiovascular risk and do not include prehospital information that is substantially important for early decision making. The aim of the study was to define clinical parameters in the prehospital setting, which may affect clinical ou...
Autores principales: | , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8624120/ https://www.ncbi.nlm.nih.gov/pubmed/34830638 http://dx.doi.org/10.3390/jcm10225355 |
_version_ | 1784606095990325248 |
---|---|
author | Elbaz-Greener, Gabby Carasso, Shemy Maor, Elad Gallimidi, Lior Yarkoni, Merav Wijeysundera, Harindra C. Abend, Yitzhak Dagan, Yinon Lerman, Amir Amir, Offer |
author_facet | Elbaz-Greener, Gabby Carasso, Shemy Maor, Elad Gallimidi, Lior Yarkoni, Merav Wijeysundera, Harindra C. Abend, Yitzhak Dagan, Yinon Lerman, Amir Amir, Offer |
author_sort | Elbaz-Greener, Gabby |
collection | PubMed |
description | (1) Introduction: Most studies rely on in-hospital data to predict cardiovascular risk and do not include prehospital information that is substantially important for early decision making. The aim of the study was to define clinical parameters in the prehospital setting, which may affect clinical outcomes. (2) Methods: In this population-based study, we performed a retrospective analysis of emergency calls that were made by patients to the largest private emergency medical services (EMS) in Israel, SHL Telemedicine Ltd., who were treated on-site by the EMS team. Demographics, clinical characteristics, and clinical outcomes were analyzed. Mortality was evaluated at three time points: 1, 3, and 12 months’ follow-up. The first EMS prehospital measurements of the systolic blood pressure (SBP) were recorded and analyzed. Logistic regression analyses were performed. (3) Results: A total of 64,320 emergency calls were included with a follow-up of 12 months post index EMS call. Fifty-five percent of patients were men and the mean age was 70.2 ± 13.1 years. During follow-up of 12 months, 7.6% of patients died. Age above 80 years (OR 3.34; 95% CI 3.03–3.69, p < 0.005), first EMS SBP ≤ 130 mm Hg (OR 2.61; 95% CI 2.36–2.88, p < 0.005), dyspnea at presentation (OR 2.55; 95% CI 2.29–2.83, p < 0001), and chest pain with ischemic ECG changes (OR 1.95; 95% CI 1.71–2.23, p < 0.001) were the highest predictors of 1 month mortality and remained so for mortality at 3 and 12 months. In contrast, history of hypertension and first EMS prehospital SBP ≥ 160 mm Hg were significantly associated with decreased mortality at 1, 3 and 12 months. (4) Conclusions: We identified risk predictors for all-cause mortality in a large cohort of patients during prehospital EMS calls. Age over 80 years, first EMS-documented prehospital SBP < 130 mm Hg, and dyspnea at presentation were the most profound risk predictors for short- and long-term mortality. The current study demonstrates that in prehospital EMS call settings, several parameters can be used to improve prioritization and management of high-risk patients. |
format | Online Article Text |
id | pubmed-8624120 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-86241202021-11-27 Clinical Predictors of Mortality in Prehospital Distress Calls by Emergency Medical Service Subscribers Elbaz-Greener, Gabby Carasso, Shemy Maor, Elad Gallimidi, Lior Yarkoni, Merav Wijeysundera, Harindra C. Abend, Yitzhak Dagan, Yinon Lerman, Amir Amir, Offer J Clin Med Article (1) Introduction: Most studies rely on in-hospital data to predict cardiovascular risk and do not include prehospital information that is substantially important for early decision making. The aim of the study was to define clinical parameters in the prehospital setting, which may affect clinical outcomes. (2) Methods: In this population-based study, we performed a retrospective analysis of emergency calls that were made by patients to the largest private emergency medical services (EMS) in Israel, SHL Telemedicine Ltd., who were treated on-site by the EMS team. Demographics, clinical characteristics, and clinical outcomes were analyzed. Mortality was evaluated at three time points: 1, 3, and 12 months’ follow-up. The first EMS prehospital measurements of the systolic blood pressure (SBP) were recorded and analyzed. Logistic regression analyses were performed. (3) Results: A total of 64,320 emergency calls were included with a follow-up of 12 months post index EMS call. Fifty-five percent of patients were men and the mean age was 70.2 ± 13.1 years. During follow-up of 12 months, 7.6% of patients died. Age above 80 years (OR 3.34; 95% CI 3.03–3.69, p < 0.005), first EMS SBP ≤ 130 mm Hg (OR 2.61; 95% CI 2.36–2.88, p < 0.005), dyspnea at presentation (OR 2.55; 95% CI 2.29–2.83, p < 0001), and chest pain with ischemic ECG changes (OR 1.95; 95% CI 1.71–2.23, p < 0.001) were the highest predictors of 1 month mortality and remained so for mortality at 3 and 12 months. In contrast, history of hypertension and first EMS prehospital SBP ≥ 160 mm Hg were significantly associated with decreased mortality at 1, 3 and 12 months. (4) Conclusions: We identified risk predictors for all-cause mortality in a large cohort of patients during prehospital EMS calls. Age over 80 years, first EMS-documented prehospital SBP < 130 mm Hg, and dyspnea at presentation were the most profound risk predictors for short- and long-term mortality. The current study demonstrates that in prehospital EMS call settings, several parameters can be used to improve prioritization and management of high-risk patients. MDPI 2021-11-17 /pmc/articles/PMC8624120/ /pubmed/34830638 http://dx.doi.org/10.3390/jcm10225355 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Elbaz-Greener, Gabby Carasso, Shemy Maor, Elad Gallimidi, Lior Yarkoni, Merav Wijeysundera, Harindra C. Abend, Yitzhak Dagan, Yinon Lerman, Amir Amir, Offer Clinical Predictors of Mortality in Prehospital Distress Calls by Emergency Medical Service Subscribers |
title | Clinical Predictors of Mortality in Prehospital Distress Calls by Emergency Medical Service Subscribers |
title_full | Clinical Predictors of Mortality in Prehospital Distress Calls by Emergency Medical Service Subscribers |
title_fullStr | Clinical Predictors of Mortality in Prehospital Distress Calls by Emergency Medical Service Subscribers |
title_full_unstemmed | Clinical Predictors of Mortality in Prehospital Distress Calls by Emergency Medical Service Subscribers |
title_short | Clinical Predictors of Mortality in Prehospital Distress Calls by Emergency Medical Service Subscribers |
title_sort | clinical predictors of mortality in prehospital distress calls by emergency medical service subscribers |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8624120/ https://www.ncbi.nlm.nih.gov/pubmed/34830638 http://dx.doi.org/10.3390/jcm10225355 |
work_keys_str_mv | AT elbazgreenergabby clinicalpredictorsofmortalityinprehospitaldistresscallsbyemergencymedicalservicesubscribers AT carassoshemy clinicalpredictorsofmortalityinprehospitaldistresscallsbyemergencymedicalservicesubscribers AT maorelad clinicalpredictorsofmortalityinprehospitaldistresscallsbyemergencymedicalservicesubscribers AT gallimidilior clinicalpredictorsofmortalityinprehospitaldistresscallsbyemergencymedicalservicesubscribers AT yarkonimerav clinicalpredictorsofmortalityinprehospitaldistresscallsbyemergencymedicalservicesubscribers AT wijeysunderaharindrac clinicalpredictorsofmortalityinprehospitaldistresscallsbyemergencymedicalservicesubscribers AT abendyitzhak clinicalpredictorsofmortalityinprehospitaldistresscallsbyemergencymedicalservicesubscribers AT daganyinon clinicalpredictorsofmortalityinprehospitaldistresscallsbyemergencymedicalservicesubscribers AT lermanamir clinicalpredictorsofmortalityinprehospitaldistresscallsbyemergencymedicalservicesubscribers AT amiroffer clinicalpredictorsofmortalityinprehospitaldistresscallsbyemergencymedicalservicesubscribers |