Evidence map›Paper›PMID 29303796›Full record

ArticleCritical care medicine2018

A Comparative Analysis of Sepsis Identification Methods in an Electronic Database.

Alistair E W Johnson, Jerome Aboab, Jesse D Raffa, Tom J Pollard, Rodrigo O Deliberato, Leo A Celi, David J Stone

Abstract read
In one paragraph

Article in Critical care medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 90 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
90citing papers in PubMed, 2 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

90 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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30 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Alistair E W JohnsonMIT Critical Data, Cambridge, MA.
Jerome AboabMIT Critical Data, Cambridge, MA.
Jesse D RaffaMIT Critical Data, Cambridge, MA.
Tom J PollardMIT Critical Data, Cambridge, MA.
Rodrigo O DeliberatoMIT Critical Data, Cambridge, MA.
Leo A CeliMIT Critical Data, Cambridge, MA.
David J StoneMIT Critical Data, Cambridge, MA.

Funding

Research Resource for Complex Physiologic SignalsR01GM104987 · NIGMS · BETH ISRAEL DEACONESS MEDICAL CENTER · PI GOLDBERGER, ARY LOUIS, MARK, ROGER GREENWOOD · 2012 to 2019
$5.8M
Critical Care Informatics: Ethical considerations around the use and sharing of health-related dataR01EB017205 · NIBIB · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI CELI, LEO ANTHONY G, MARK, ROGER GREENWOOD · 2014 to 2021
$3.8M
NIBIB NIH HHS R01 EB017205NIGMS NIH HHS R01 GM104987
6 · The paper itself

Abstract

objectivesTo evaluate the relative validity of criteria for the identification of sepsis in an ICU database.

designRetrospective cohort study of adult ICU admissions from 2008 to 2012.

settingTertiary teaching hospital in Boston, MA. PATIENTS: Initial admission of all adult patients to noncardiac surgical ICUs.

interventionsComparison of five different algorithms for retrospectively identifying sepsis, including the Sepsis-3 criteria. MEASUREMENTS AND MAIN

results11,791 of 23,620 ICU admissions (49.9%) met criteria for the study. Within this subgroup, 59.9% were suspected of infection on ICU admission, 75.2% of admissions had Sequential Organ Failure Assessment greater than or equal to 2, and 49.1% had both suspicion of infection and Sequential Organ Failure Assessment greater than or equal to 2 thereby meeting the Sepsis-3 criteria. The area under the receiver operator characteristic of Sequential Organ Failure Assessment (0.74) for hospital mortality was consistent with previous studies of the Sepsis-3 criteria. The Centers for Disease Control and Prevention, Angus, Martin, Centers for Medicare & Medicaid Services, and explicit coding methods for identifying sepsis revealed respective sepsis incidences of 31.9%, 28.6%, 14.7%, 11.0%, and 9.0%. In-hospital mortality increased with decreasing cohort size, ranging from 30.1% (explicit codes) to 14.5% (Sepsis-3 criteria). Agreement among the criteria was acceptable (Cronbach's alpha, 0.40-0.62).

conclusionsThe new organ dysfunction-based Sepsis-3 criteria have been proposed as a clinical method for identifying sepsis. These criteria identified a larger, less severely ill cohort than that identified by previously used administrative definitions. The Sepsis-3 criteria have several advantages over prior methods, including less susceptibility to coding practices changes, provision of temporal context, and possession of high construct validity. However, the Sepsis-3 criteria also present new challenges, especially when calculated retrospectively. Future studies on sepsis should recognize the differences in outcome incidence among identification methods and contextualize their findings according to the different cohorts identified.

Indexed as

Severity of Illness IndexAgedAged, 80 and overAge FactorsAlgorithmsBostonClinical CodingDatabases, FactualFemaleHospital MortalityHospitals, TeachingHumansIntensive Care UnitsLength of StayMaleMiddle Aged

Identifiers

PMID29303796
PMCPMC5851804

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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.