Evidence map›Paper›PMID 28903154›Full record

ArticleJAMA2017

Incidence and Trends of Sepsis in US Hospitals Using Clinical vs Claims Data, 2009-2014.

Chanu Rhee, Raymund Dantes, Lauren Epstein, David J Murphy, Christopher W Seymour, Theodore J Iwashyna, Sameer S Kadri, Derek C Angus, Robert L Danner, Anthony E Fiore and 11 more

5 registry-linked trialsAbstract readComparative Study
In one paragraph

Article in JAMA, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 5 registered trials, which are not on this map. Cited by 1,015 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1,015citing papers in PubMed, 6 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.

NCT02085291 phase4completednot on this map

The Effect of Fluids and Norepinephrine for Mean Arterial Pressure Titration to Patients' Usual Levels on the Microcirculation of Initial Resuscitated Hypertensive Septic Shock Patients.

TypeinterventionalSponsorSoutheast University, ChinaRan2014 to 2017Enrolled24ConditionsSeptic Shock, HypertensionArmsNorepinephrine, Crystalloid
NCT04169412 completednot on this mapstarted 2019, after this paper: background citation

Resuscitation Failure, Protein Carbonyl and Receptor Interacting Protein Kinase 3 as Mortality Predictor in Septic Patient

Typeobservational_patient_registrySponsorUniversitas SriwijayaRan2019 to 2019Enrolled72ConditionsSepsisArmsBlood Collection
NCT05193045 unknown statusnot on this mapstarted 2021, after this paper: background citation

Prognosis of Klebsiella ESBL Sepsis: Role of 2-HYDRoxy-myristate in Endotoxin Structure

TypeobservationalSponsorFondation Hôpital Saint-JosephRan2021 to 2023Enrolled28ConditionsKlebsiella Infections
NCT05686577 completednot on this mapstarted 2022, after this paper: background citation

Comment Diminuer Les hémocultures Inutiles : Construction et Validation d'un Score prédictif de positivité Des hémocultures en réanimation.

TypeobservationalSponsorUniversity Hospital, ToursRan2022 to 2023Enrolled2,411ConditionsInfection, Bacterial, Infection, Fungal, BacteremiaArmsno intervention
NCT07167173 not yet recruitingnot on this mapstarted 2025, after this paper: background citation

Predictive Model for Multidrug Resistance in Patients Admitted to the Emergency Department With Sepsis

TypeobservationalSponsorHospital Italiano de Buenos AiresRan2025 to 2025Enrolled10,000ConditionsSepsis, Septic Shock
3 · Its place in the literature

Who cites it

1,015 citing papers in PubMed, 6 syntheses or guidelines pooled it.

  1. Pooled it
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  6. Corticosteroids for treating sepsis in children and adults.The Cochrane database of systematic reviews · 2025
    Pooled it
  7. Article
  8. 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
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955 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

21 authors.

Chanu RheeDepartment of Population Medicine, Harvard Medical School/Harvard Pilgrim Health Care Institute, Boston, Massachusetts.
Raymund DantesDivision of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia.
Lauren EpsteinDivision of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia.
David J MurphyDivision of Pulmonary, Allergy, Critical Care and Sleep Medicine, Department of Medicine, Emory University School of Medicine, and Emory Critical Care Center, Atlanta, Georgia.
Christopher W SeymourClinical Research, Investigation and Systems Modeling of Acute illness (CRISMA) Center, Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.
Theodore J IwashynaDepartment of Internal Medicine, University of Michigan, Ann Arbor.
Sameer S KadriCritical Care Medicine Department, Clinical Center, National Institutes of Health, Bethesda, Maryland.
Derek C AngusClinical Research, Investigation and Systems Modeling of Acute illness (CRISMA) Center, Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.
Robert L DannerCritical Care Medicine Department, Clinical Center, National Institutes of Health, Bethesda, Maryland.
Anthony E FioreDivision of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia.
John A JerniganDivision of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia.
Greg S MartinDivision of Pulmonary, Allergy, Critical Care and Sleep Medicine, Department of Medicine, Emory University School of Medicine, and Emory Critical Care Center, Atlanta, Georgia.
Edward SeptimusHospital Corporation of America, Nashville, Tennessee.
David K WarrenDepartment of Medicine, Washington University School of Medicine, St Louis, Missouri.
Anita KarczInstitute for Health Metrics, Burlington, Massachusetts.
Christina ChanDepartment of Population Medicine, Harvard Medical School/Harvard Pilgrim Health Care Institute, Boston, Massachusetts.
John T MenchacaDepartment of Population Medicine, Harvard Medical School/Harvard Pilgrim Health Care Institute, Boston, Massachusetts.
Rui WangDepartment of Population Medicine, Harvard Medical School/Harvard Pilgrim Health Care Institute, Boston, Massachusetts.
Susan GruberDepartment of Population Medicine, Harvard Medical School/Harvard Pilgrim Health Care Institute, Boston, Massachusetts.
Michael KlompasDepartment of Population Medicine, Harvard Medical School/Harvard Pilgrim Health Care Institute, Boston, Massachusetts.
CDC Prevention Epicenter Program

Funding

Sepsis subtypes: biology, treatment, and bedside applicationR35GM119519 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Christopher W. Seymour · 2016 to 2026
$4.9M
Objective Evaluation of Variation in Sepsis Incidence, Mortality, and CareK08HS025008 · AHRQ · HARVARD PILGRIM HEALTH CARE, INC. · PI RHEE, CHANU · 2017 to 2019
$450k
Preclinical and Clinical Investigations of Severe Infection and Critical Illness ZIACL008060 · CLC · CLINICAL CENTER · PI DANNER, ROBERT L · 2009 to 2025
$0k
Big Data - Epidemiology of Critical Illness and SepsisZIACL090045 · CLC · CLINICAL CENTER · PI KADRI, SAMEER · 2017 to 2025
$0k
AHRQ HHS K08 HS025008NCEZID CDC HHS U54 CK000172NIGMS NIH HHS R35 GM119519
6 · The paper itself

Abstract

Importance: Estimates from claims-based analyses suggest that the incidence of sepsis is increasing and mortality rates from sepsis are decreasing. However, estimates from claims data may lack clinical fidelity and can be affected by changing diagnosis and coding practices over time. Objective: To estimate the US national incidence of sepsis and trends using detailed clinical data from the electronic health record (EHR) systems of diverse hospitals. Design, Setting, and Population: Retrospective cohort study of adult patients admitted to 409 academic, community, and federal hospitals from 2009-2014. Exposures: Sepsis was identified using clinical indicators of presumed infection and concurrent acute organ dysfunction, adapting Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3) criteria for objective and consistent EHR-based surveillance. Main Outcomes and Measures: Sepsis incidence, outcomes, and trends from 2009-2014 were calculated using regression models and compared with claims-based estimates using International Classification of Diseases, Ninth Revision, Clinical Modification codes for severe sepsis or septic shock. Case-finding criteria were validated against Sepsis-3 criteria using medical record reviews. Results: A total of 173 690 sepsis cases (mean age, 66.5 [SD, 15.5] y; 77 660 [42.4%] women) were identified using clinical criteria among 2 901 019 adults admitted to study hospitals in 2014 (6.0% incidence). Of these, 26 061 (15.0%) died in the hospital and 10 731 (6.2%) were discharged to hospice. From 2009-2014, sepsis incidence using clinical criteria was stable (+0.6% relative change/y [95% CI, -2.3% to 3.5%], P = .67) whereas incidence per claims increased (+10.3%/y [95% CI, 7.2% to 13.3%], P < .001). In-hospital mortality using clinical criteria declined (-3.3%/y [95% CI, -5.6% to -1.0%], P = .004), but there was no significant change in the combined outcome of death or discharge to hospice (-1.3%/y [95% CI, -3.2% to 0.6%], P = .19). In contrast, mortality using claims declined significantly (-7.0%/y [95% CI, -8.8% to -5.2%], P < .001), as did death or discharge to hospice (-4.5%/y [95% CI, -6.1% to -2.8%], P < .001). Clinical criteria were more sensitive in identifying sepsis than claims (69.7% [95% CI, 52.9% to 92.0%] vs 32.3% [95% CI, 24.4% to 43.0%], P < .001), with comparable positive predictive value (70.4% [95% CI, 64.0% to 76.8%] vs 75.2% [95% CI, 69.8% to 80.6%], P = .23). Conclusions and Relevance: In clinical data from 409 hospitals, sepsis was present in 6% of adult hospitalizations, and in contrast to claims-based analyses, neither the incidence of sepsis nor the combined outcome of death or discharge to hospice changed significantly between 2009-2014. The findings also suggest that EHR-based clinical data provide more objective estimates than claims-based data for sepsis surveillance.

Indexed as

Electronic Health RecordsAdultAgedClinical CodingFemaleHospitalizationHospital MortalityHumansIncidenceInsurance Claim ReportingMaleMedical AuditMiddle AgedMortalityRetrospective StudiesSepsis

Identifiers

PMID28903154
PMCPMC5710396

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Registered trials

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.