Evidence map›Paper›PMID 39349049›Full record

ArticleOpen heart2024

Prehospital factors predicting mortality in patients with shock: state-wide linkage study.

Amminadab L Eliakundu, Jason E Bloom, Jocasta Ball, Emily Nehme, Daniel Okyere, Stephane Heritier, Aleksandr Voskoboinik, Luke Dawson, Shelley Cox, David Anderson and 6 more

Abstract readMulticenter Study
In one paragraph

Article in Open heart, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Amminadab L EliakunduSchool of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.ORCID 0000-0002-9160-9422
Jason E BloomSchool of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.ORCID 0000-0001-8838-0332
Jocasta BallSchool of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.ORCID 0000-0002-1512-4255
Emily NehmeCentre for Research and Evaluation, Ambulance Victoria, Blackburn, Victoria, Australia.
Daniel OkyereSchool of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.
Stephane HeritierSchool of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.
Aleksandr VoskoboinikDepartment of Cardiology, The Alfred Hospital, Prahran, Victoria, Australia.
Luke DawsonSchool of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.ORCID 0000-0003-3789-5808
Shelley CoxCentre for Research and Evaluation, Ambulance Victoria, Blackburn, Victoria, Australia.
David AndersonDepartment of Cardiology, The Alfred Hospital, Prahran, Victoria, Australia.
Aidan BurrellDepartment of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.
David PilcherDepartment of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.
Derek P ChewVictorian Heart Institute, Monash University, Blackburn, Victoria, Australia.
David KayeDepartment of Cardiology, The Alfred Hospital, Prahran, Victoria, Australia.
Ziad NehmeCentre for Research and Evaluation, Ambulance Victoria, Blackburn, Victoria, Australia.ORCID 0000-0003-2432-1645
Dion StubSchool of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia d.stub@alfred.org.au.ORCID 0000-0001-8686-2709

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPatients with shock treated by emergency medical services (EMS) have high morbidity and mortality. Knowledge of prehospital factors predicting outcomes in patients with shock remains limited. We aimed to describe the prehospital predictors of mortality in patients with non-traumatic shock transported to hospital by EMS.

methodThis is a retrospective cohort study of consecutive ambulance attendances for non-traumatic shock in Victoria, Australia (January 2015-June 2019) linked with government-held administrative data (emergency, admissions and mortality records). Predictors of 30-day mortality were assessed using Cox proportional regressions. The primary outcome was 30-day all-cause mortality.

resultsOverall, 21 334 patients with non-traumatic shock (median age 69 years, 54.8% female) were successfully linked with state administrative records. Among this cohort, 9 149 (43%) patients died within 30-days. Compared with survivors, non-survivors had a longer median on-scene time: 60 (35-98) versus 30 (19-50), p <0.001. Non-survivors were more likely to be older (median age in years: 74 (61-84) vs 65 (47-78), p<0.001), had prehospital cardiac arrest requiring cardiopulmonary resuscitation (adjusted HR (aHR)=6.26, 95% CI 5.87, 6.69) and had prehospital intubation (aHR=1.07, CI 1.00, 1.14). Reduced 30-day mortality was associated with administration of epinephrine (aHR=0.66, CI 0.62, 0.71) and systolic blood pressures above 80 mm Hg in the prehospital setting.

conclusionThe 30-day mortality from non-traumatic shock is high at 43%. Independent predictors of mortality included age, prehospital cardiac arrest and endotracheal intubation. Interventions that target reversible causes of short-term mortality in patients with non-traumatic shock are a high priority.

Indexed as

Emergency Medical ServicesAgedAged, 80 and overCardiopulmonary ResuscitationFemaleHumansMaleMiddle AgedPrognosisRetrospective StudiesRisk AssessmentRisk FactorsShockSurvival RateTime FactorsVictoriaEpidemiologyHealth ServicesOut-of-Hospital Cardiac Arrest

Identifiers

PMID39349049
PMCPMC11448143

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.