Evidence map›Paper›PMID 37531612›Full record

ArticleClinical infectious diseases : an official publication of the Infectious Diseases Society of America2023

Risk of Misleading Conclusions in Observational Studies of Time-to-Antibiotics and Mortality in Suspected Sepsis.

Theodore R Pak, Jessica Young, Caroline S McKenna, Anna Agan, Laura DelloStritto, Michael R Filbin, Sayon Dutta, Sameer S Kadri, Edward J Septimus, Chanu Rhee and 1 more

Abstract read
In one paragraph

Article in Clinical infectious diseases : an official publication of the Infectious Diseases Society of America, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 1 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

31 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Trial
  4. Time to Antibiotics and Mortality in Immunocompromised Versus Non-immunocompromised Patients With Suspected Sepsis.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2026
    Article
  5. Observational
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Association Between Delayed Broad-Spectrum Gram-negative Antibiotics and Clinical Outcomes: How Much Does Getting It Right With Empiric Antibiotics Matter?Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2025
    Article
  15. Article
  16. Article
  17. Association Between the Sequence of β-Lactam and Vancomycin Administration and Mortality in Patients With Suspected Sepsis.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2025
    Article
  18. Article
  19. Article
  20. Observational
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

11 authors.

Theodore R PakDepartment of Population Medicine, Harvard Medical School and Harvard Pilgrim Healthcare Institute, Boston, Massachusetts, USA.ORCID 0000-0002-1676-2523
Jessica YoungDepartment of Population Medicine, Harvard Medical School and Harvard Pilgrim Healthcare Institute, Boston, Massachusetts, USA.
Caroline S McKennaDepartment of Population Medicine, Harvard Medical School and Harvard Pilgrim Healthcare Institute, Boston, Massachusetts, USA.
Anna AganDepartment of Population Medicine, Harvard Medical School and Harvard Pilgrim Healthcare Institute, Boston, Massachusetts, USA.
Laura DelloStrittoDepartment of Population Medicine, Harvard Medical School and Harvard Pilgrim Healthcare Institute, Boston, Massachusetts, USA.
Michael R FilbinDepartment of Emergency Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA.
Sayon DuttaDepartment of Emergency Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA.ORCID 0000-0002-0381-6860
Sameer S KadriCritical Care Medicine, National Institutes of Health Clinical Center, Bethesda, Maryland, USA.
Edward J SeptimusDepartment of Population Medicine, Harvard Medical School and Harvard Pilgrim Healthcare Institute, Boston, Massachusetts, USA.
Chanu RheeDepartment of Population Medicine, Harvard Medical School and Harvard Pilgrim Healthcare Institute, Boston, Massachusetts, USA.ORCID 0000-0002-9537-4245
Michael KlompasDepartment of Population Medicine, Harvard Medical School and Harvard Pilgrim Healthcare Institute, Boston, Massachusetts, USA.

Funding

INFECTIOUS DISEASE AND BASIC MICROBIOLOGICAL MECHANISMST32AI007061 · NIAID · MASSACHUSETTS GENERAL HOSPITAL · PI Marcia B Goldberg · 1985 to 2026
$12.1M
Developing Evidence-Based Sepsis Time Zero Criteria and Quality Metrics Using Electronic Health Record DataR01HS027170 · AHRQ · HARVARD PILGRIM HEALTH CARE, INC. · PI KLOMPAS, MICHAEL, RHEE, CHANU · 2020 to 2024
$2.4M
Big Data - Epidemiology of Critical Illness and SepsisZIACL090045 · CLC · CLINICAL CENTER · PI KADRI, SAMEER · 2017 to 2025
$0k
AHRQ HHS R01 HS027170CDC HHSNCEZID CDC HHS U54 CK000611NIAID NIH HHS T32 AI007061
6 · The paper itself

Abstract

backgroundInfluential studies conclude that each hour until antibiotics increases mortality in sepsis. However, these analyses often (1) adjusted for limited covariates, (2) included patients with long delays until antibiotics, (3) combined sepsis and septic shock, and (4) used linear models presuming each hour delay has equal impact. We evaluated the effect of these analytic choices on associations between time-to-antibiotics and mortality.

methodsWe retrospectively identified 104 248 adults admitted to 5 hospitals from 2015-2022 with suspected infection (blood culture collection and intravenous antibiotics ≤24 h of arrival), including 25 990 with suspected septic shock and 23 619 with sepsis without shock. We used multivariable regression to calculate associations between time-to-antibiotics and in-hospital mortality under successively broader confounding-adjustment, shorter maximum time-to-antibiotic intervals, stratification by illness severity, and removing assumptions of linear hourly associations.

resultsChanging covariates, maximum time-to-antibiotics, and severity stratification altered the magnitude, direction, and significance of observed associations between time-to-antibiotics and mortality. In a fully adjusted model of patients treated ≤6 hours, each hour was associated with higher mortality for septic shock (adjusted odds ratio [aOR]: 1.07; 95% CI: 1.04-1.11) but not sepsis without shock (aOR: 1.03; .98-1.09) or suspected infection alone (aOR: .99; .94-1.05). Modeling each hour separately confirmed that every hour of delay was associated with increased mortality for septic shock, but only delays >6 hours were associated with higher mortality for sepsis without shock.

conclusionsAssociations between time-to-antibiotics and mortality in sepsis are highly sensitive to analytic choices. Failure to adequately address these issues can generate misleading conclusions.

Indexed as

SepsisShock, SepticAdultAnti-Bacterial AgentsHospital MortalityHumansRetrospective StudiesTime FactorsAnti-Bacterial Agentscohort studyquality measuresSurviving Sepsis Campaigntime-to-intervention

Identifiers

PMID37531612
PMCPMC10686960

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.