Evidence map›Paper›PMID 32337048›Full record

ArticleJournal of intensive care2020

Antimicrobials administration time in patients with suspected sepsis: is faster better? An analysis by propensity score.

Johana Ascuntar, Deibie Mendoza, Fabián Jaimes

Open access · goldAbstract read
In one paragraph

Article in Journal of intensive care, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.5field-weighted citation impact, top 17% of its field
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

7 citing papers in PubMed, 15 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Johana Ascuntar1GRAEPIC-Clinical Epidemiology Academic Group (Grupo Académico de Epidemiología Clínica), the University of Antioquia, Medellín, Colombia.
Deibie Mendoza2University of Antioquia, Medellín, Colombia.
Fabián Jaimes1GRAEPIC-Clinical Epidemiology Academic Group (Grupo Académico de Epidemiología Clínica), the University of Antioquia, Medellín, Colombia.
Universidad de Antioquia · COHospital Universitario de San Vicente Fundación · CO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEarly use of antimicrobials is a critical intervention in the treatment of patients with sepsis. The exact time of initiation is controversial and its early administration may be a difficult task in crowded emergency departments (ED). The aim of this study was to estimate, using a matched propensity score, the effect on hospital mortality of administration of antimicrobials within 1 or 3 hours, in patients admitted to the ED with sepsis.

methodsThis was a secondary analysis of a multicenter prospective cohort. Patients included in the study were older than 18 years, hospitalized between 2014 and 2016 with suspected sepsis, and admitted to ED of three tertiary care university hospitals in Medellín, Colombia. A propensity score analysis for administration of antimicrobials, both within 1 and 3 h of admission by the ED, was fitted with 28 variables related with clinical attention and physiological changes. As a sensitivity analysis, a logistic regression model was fitted for antimicrobial use adjusted both by propensity score and confounding variables.

resultsThe study cohort was composed of 2454 patients with a median age of 62 years (IQR = 46-74). Among them, 32% (

conclusionsDespite the obvious constraints given for sample size and residual confounding, our results suggest that we need a more comprehensive approach to sepsis and its treatment, considering early detection, multiple interventions, and goals beyond the simple time-to-antimicrobials.

Indexed as

antibioticsantimicrobialsin-hospital mortalitypropensity scoreSepsis

Identifiers

PMID32337048
PMCPMC7178597
OpenAlexW3018937259

What OpenQuestion holds

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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.