Evidence map›Paper›PMID 36652245›Full record

ArticleJAMA network open2023

Defining Posttraumatic Sepsis for Population-Level Research.

Katherine Stern, Qian Qiu, Michael Weykamp, Grant O'Keefe, Scott C Brakenridge

Abstract read
In one paragraph

Article in JAMA network open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–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

5 citing papers in PubMed.

  1. Observational
  2. Article
  3. Observational
  4. Review
  5. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Katherine SternDivision of Trauma, Burn, and Critical Care, Department of Surgery, University of Washington, Seattle.
Qian QiuHarborview Injury Prevention Center, University of Washington, Seattle.
Michael WeykampDivision of Trauma, Burn, and Critical Care, Department of Surgery, University of Washington, Seattle.
Grant O'KeefeDivision of Trauma, Burn, and Critical Care, Department of Surgery, University of Washington, Seattle.
Scott C BrakenridgeDivision of Trauma, Burn, and Critical Care, Department of Surgery, University of Washington, Seattle.

Funding

Surgery Research Training ProgramT32GM121290 · NIGMS · UNIVERSITY OF WASHINGTON · PI GRANT E O'KEEFE · 2017 to 2026
$2.8M
Immunological Endotyping of Chronic Critical Illness after Severe Trauma or Sepsis: Administrative SupplementR35GM142481 · NIGMS · UNIVERSITY OF WASHINGTON · PI BRAKENRIDGE, SCOTT CHARLES · 2021 to 2025
$2.0M
NIGMS NIH HHS R35 GM142481NIGMS NIH HHS T32 GM121290
6 · The paper itself

Abstract

Importance: Multiple classification methods are used to identify sepsis from existing data. In the trauma population, it is unknown how administrative methods compare with clinical criteria for sepsis classification. Objectives: To characterize the agreement between 3 approaches to sepsis classification among critically ill patients with trauma and compare the sepsis-associated risk of adverse outcomes when each method was used to define sepsis. Design, Setting, and Participants: This retrospective cohort study used data collected between January 1, 2012, and December 31, 2020, from patients aged 16 years or older with traumatic injury, admitted to the intensive care unit of a single-institution level 1 trauma center and requiring invasive mechanical ventilation for at least 3 days. Statistical analysis was conducted from August 1, 2021, to March 31, 2022. Exposure: Hospital-acquired sepsis, as classified by 3 methods: a novel automated clinical method based on data from the electronic health record, the National Trauma Data Bank (NTDB), and explicit and implicit medical billing codes. Main Outcomes and Measures: The primary outcomes were chronic critical illness and in-hospital mortality. Secondary outcomes included number of days in an intensive care unit, number of days receiving mechanical ventilation, discharge to a skilled nursing or long-term care facility, and discharge to home without assistance. Results: Of 3194 patients meeting inclusion criteria, the median age was 49 years (IQR, 31-64 years), 2380 (74%) were male, and 2826 (88%) sustained severe blunt injury (median Injury Severity Score, 29 [IQR, 21-38]). Sepsis was identified in 747 patients (23%) meeting automated clinical criteria, 118 (4%) meeting NTDB criteria, and 529 (17%) using medical billing codes. The Light κ value for 3-way agreement was 0.16 (95% CI, 0.14-0.19). The adjusted relative risk of chronic critical illness was 9.9 (95% CI, 8.0-12.3) for sepsis identified by automated clinical criteria, 5.0 (95% CI, 3.4-7.3) for sepsis identified by the NTDB, and 4.5 (95% CI, 3.6-5.6) for sepsis identified using medical billing codes. The adjusted relative risk for in-hospital mortality was 1.3 (95% CI, 1.0-1.6) for sepsis identified by automated clinical criteria, 2.7 (95% CI, 1.7-4.3) for sepsis identified by the NTDB, and 1.0 (95% CI, 0.7-1.2) for sepsis identified using medical billing codes. Conclusions and Relevance: In this cohort study of critically ill patients with trauma, administrative methods misclassified sepsis and underestimated the incidence and severity of sepsis compared with an automated clinical method using data from the electronic health record. This study suggests that an automated approach to sepsis classification consistent with Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3) clinical criteria is feasible and may improve existing approaches to health services and population-based research in this population.

Indexed as

Critical IllnessSepsisCohort StudiesFemaleHospital MortalityHumansMaleMiddle AgedRetrospective Studies

Identifiers

PMID36652245
PMCPMC9857630

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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.