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...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Gabby Elbaz-Greener, Shemy Carasso, Elad Maor, Lior Gallimidi, Merav Yarkoni, Harindra C. Wijeysundera, Yitzhak Abend, Yinon Dagan, Amir Lerman, Offer Amir
Formato: article
Lenguaje:EN
Publicado: MDPI AG 2021
Materias:
R
Acceso en línea:https://doaj.org/article/81554116e7f64650ac9f241542bd4842
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
id oai:doaj.org-article:81554116e7f64650ac9f241542bd4842
record_format dspace
spelling oai:doaj.org-article:81554116e7f64650ac9f241542bd48422021-11-25T18:02:02ZClinical Predictors of Mortality in Prehospital Distress Calls by Emergency Medical Service Subscribers10.3390/jcm102253552077-0383https://doaj.org/article/81554116e7f64650ac9f241542bd48422021-11-01T00:00:00Zhttps://www.mdpi.com/2077-0383/10/22/5355https://doaj.org/toc/2077-0383(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, <i>p</i> < 0.005), first EMS SBP ≤ 130 mm Hg (OR 2.61; 95% CI 2.36–2.88, <i>p</i> < 0.005), dyspnea at presentation (OR 2.55; 95% CI 2.29–2.83, <i>p</i> < 0001), and chest pain with ischemic ECG changes (OR 1.95; 95% CI 1.71–2.23, <i>p</i> < 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.Gabby Elbaz-GreenerShemy CarassoElad MaorLior GallimidiMerav YarkoniHarindra C. WijeysunderaYitzhak AbendYinon DaganAmir LermanOffer AmirMDPI AGarticleprehospital mortalityoctogenarianshypertension paradoxoutcomeMedicineRENJournal of Clinical Medicine, Vol 10, Iss 5355, p 5355 (2021)
institution DOAJ
collection DOAJ
language EN
topic prehospital mortality
octogenarians
hypertension paradox
outcome
Medicine
R
spellingShingle prehospital mortality
octogenarians
hypertension paradox
outcome
Medicine
R
Gabby Elbaz-Greener
Shemy Carasso
Elad Maor
Lior Gallimidi
Merav Yarkoni
Harindra C. Wijeysundera
Yitzhak Abend
Yinon Dagan
Amir Lerman
Offer Amir
Clinical Predictors of Mortality in Prehospital Distress Calls by Emergency Medical Service Subscribers
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, <i>p</i> < 0.005), first EMS SBP ≤ 130 mm Hg (OR 2.61; 95% CI 2.36–2.88, <i>p</i> < 0.005), dyspnea at presentation (OR 2.55; 95% CI 2.29–2.83, <i>p</i> < 0001), and chest pain with ischemic ECG changes (OR 1.95; 95% CI 1.71–2.23, <i>p</i> < 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 article
author Gabby Elbaz-Greener
Shemy Carasso
Elad Maor
Lior Gallimidi
Merav Yarkoni
Harindra C. Wijeysundera
Yitzhak Abend
Yinon Dagan
Amir Lerman
Offer Amir
author_facet Gabby Elbaz-Greener
Shemy Carasso
Elad Maor
Lior Gallimidi
Merav Yarkoni
Harindra C. Wijeysundera
Yitzhak Abend
Yinon Dagan
Amir Lerman
Offer Amir
author_sort Gabby Elbaz-Greener
title 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_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_sort clinical predictors of mortality in prehospital distress calls by emergency medical service subscribers
publisher MDPI AG
publishDate 2021
url https://doaj.org/article/81554116e7f64650ac9f241542bd4842
work_keys_str_mv AT gabbyelbazgreener clinicalpredictorsofmortalityinprehospitaldistresscallsbyemergencymedicalservicesubscribers
AT shemycarasso clinicalpredictorsofmortalityinprehospitaldistresscallsbyemergencymedicalservicesubscribers
AT eladmaor clinicalpredictorsofmortalityinprehospitaldistresscallsbyemergencymedicalservicesubscribers
AT liorgallimidi clinicalpredictorsofmortalityinprehospitaldistresscallsbyemergencymedicalservicesubscribers
AT meravyarkoni clinicalpredictorsofmortalityinprehospitaldistresscallsbyemergencymedicalservicesubscribers
AT harindracwijeysundera clinicalpredictorsofmortalityinprehospitaldistresscallsbyemergencymedicalservicesubscribers
AT yitzhakabend clinicalpredictorsofmortalityinprehospitaldistresscallsbyemergencymedicalservicesubscribers
AT yinondagan clinicalpredictorsofmortalityinprehospitaldistresscallsbyemergencymedicalservicesubscribers
AT amirlerman clinicalpredictorsofmortalityinprehospitaldistresscallsbyemergencymedicalservicesubscribers
AT offeramir clinicalpredictorsofmortalityinprehospitaldistresscallsbyemergencymedicalservicesubscribers
_version_ 1718411689988194304