Evidence map›Paper›PMID 28385107›Full record

ArticleJournal of intensive care medicine2018

Association of Household Income Level and In-Hospital Mortality in Patients With Sepsis: A Nationwide Retrospective Cohort Analysis.

Barret Rush, Katie Wiskar, Leo Anthony Celi, Keith R Walley, James A Russell, Robert C McDermid, John H Boyd

Abstract read
In one paragraph

Article in Journal of intensive care medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
1.2field-weighted citation impact, top 21% 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

22 citing papers in PubMed, 1 synthesis or guideline pooled it, 49 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. The Global Burden of Sepsis and Septic Shock.Epidemiologia (Basel, Switzerland) · 2024
    Review
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

7 authors at 3 institutions in 2 countries.

Barret Rush1 Division of Critical Care Medicine, Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.
Katie Wiskar1 Division of Critical Care Medicine, Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.
Leo Anthony Celi5 Beth Israel Deaconess Medical Center, Boston, MA, USA.
Keith R Walley3 Centre for Heart Lung Innovation (HLI), University of British Columbia, Vancouver, British Columbia, Canada.
James A Russell3 Centre for Heart Lung Innovation (HLI), University of British Columbia, Vancouver, British Columbia, Canada.
Robert C McDermid1 Division of Critical Care Medicine, Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.
John H Boyd3 Centre for Heart Lung Innovation (HLI), University of British Columbia, Vancouver, British Columbia, Canada.
St. Paul's Hospital · CAUniversity of British Columbia · CABeth Israel Deaconess Medical Center · US

Funding

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 EB017205
6 · The paper itself

Abstract

objectiveAssociations between low socioeconomic status (SES) and poor health outcomes have been demonstrated in a variety of conditions. However, the relationship in patients with sepsis is not well described. We investigated the association of lower household income with in-hospital mortality in patients with sepsis across the United States.

methodsRetrospective nationwide cohort analysis utilizing the Nationwide Inpatient Sample (NIS) from 2011. Patients aged 18 years or older with sepsis were included. Socioeconomic status was approximated by the median household income of the zip code in which the patient resided. Multivariate logistic modeling incorporating a validated illness severity score for sepsis in administrative data was performed.

resultsA total of 8 023 590 admissions from the 2011 NIS were examined. A total of 671 858 patients with sepsis were included in the analysis. The lowest income residents compared to the highest were younger (66.9 years, standard deviation [SD] = 16.5 vs 71.4 years, SD = 16.1, P < .01), more likely to be female (53.5% vs 51.9%, P < .01), less likely to be white (54.6% vs 76.6%, P < .01), as well as less likely to have health insurance coverage (92.8% vs 95.9%, P < .01). After controlling for severity of sepsis, residing in the lowest income quartile compared to the highest quartile was associated with a higher risk of mortality (odds ratio [OR]: 1.06, 95% confidence interval [CI]: 1.03-1.08, P < .01). There was no association seen between the second (OR: 1.02, 95% CI: 0.99-1.05, P = .14) and third (OR: 0.99, 95% CI: 0.97-1.01, P = .40) quartiles compared to the highest.

conclusionAfter adjustment for severity of illness, patients with sepsis who live in the lowest median income quartile had a higher risk of mortality compared to residents of the highest income quartile. The association between SES and mortality in sepsis warrants further investigation with more comprehensive measures of SES.

Indexed as

Hospital MortalityIncomeAgedAged, 80 and overFemaleHumansLogistic ModelsMaleRetrospective StudiesSepsisSeverity of Illness IndexSocial ClassUnited Statesepidemiologyhospital mortalityoutcomessepsis

Identifiers

PMID28385107
PMCPMC5680141
OpenAlexW2604724804

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.