Evidence map›Paper›PMID 38490774›Full record

ArticleAir medical journal

Severity-Driven Trends in Mortality in a Large Regionalized Critical Care Transport Service.

David D Salcido, Chase W Zikmund, Leonard S Weiss, Andrew Schoenling, Christian Martin-Gill, Francis X Guyette, Michael R Pinsky

Abstract read
In one paragraph

Article in Air medical journal. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

David D SalcidoDepartment of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA. Electronic address: salcidodd@upmc.edu.
Chase W ZikmundDepartment of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA.
Leonard S WeissDepartment of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA.
Andrew SchoenlingDepartment of Emergency Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA.
Christian Martin-GillDepartment of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA.
Francis X GuyetteDepartment of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA.
Michael R PinskyDepartment of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA.

Funding

Autonomous diagnosis and management of the critically ill during air transport (ADMIT)R01HL141916 · NHLBI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI PINSKY, MICHAEL R · 2019 to 2022
$2.9M
NHLBI NIH HHS R01 HL141916
6 · The paper itself

Abstract

objectiveThe epidemiology accompanying helicopter emergency medical services (HEMS) transport has evolved as agencies have matured and become integrated into regionalized health systems, as evidenced primarily by nationwide systems in Europe. System-level congruence between Europe and the United States, where HEMS is geographically fragmentary, is unclear. In this study, we provide a temporal, epidemiologic characterization of the largest standardized private, nonprofit HEMS system in the United States, STAT MedEvac.

methodsWe obtained comprehensive timing, procedure, and vital signs data from STAT MedEvac prehospital electronic patient care records for all adult patients transported to UPMC Health System hospitals in the period of January 2012 through October 2021. We linked these data with hospital electronic health records available through June 2018 to establish length of stay and vital status at discharge.

resultsWe studied 90,960 transports and matched 62.8% (n = 57,128) to the electronic health record. The average patient age was 58.6 years ( 19 years), and most were male (57.9%). The majority of cases were interfacility transports (77.6%), and the most common general medical category was nontrauma (72.7%). Sixty-one percent of all patients received a prehospital intervention. Overall, hospital mortality was 15%, and the average hospital length of stay (LOS) was 8.8 days ( 10.0 days). Observed trends over time included increases in nontrauma transports, level of severity, and in-hospital mortality. In multivariable models, case severity and medical category correlated with the outcomes of mortality and LOS.

conclusionIn the largest standardized nonprofit HEMS system in the United States, patient mortality and hospital LOS increased over time, whereas the proportion of trauma patients and scene runs decreased.

Indexed as

Air AmbulancesEmergency Medical ServicesAdultAircraftCritical CareFemaleHumansInjury Severity ScoreMaleMiddle AgedRetrospective StudiesSorbitolUnited StatesSorbitol

Identifiers

PMID38490774
PMCPMC10988775

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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.