Evidence map›Paper›PMID 37624600›Full record

ArticleJAMA network open2023

Sepsis Prediction Model for Determining Sepsis vs SIRS, qSOFA, and SOFA.

Adam R Schertz, Kristin M Lenoir, Alain G Bertoni, Beverly J Levine, Morgana Mongraw-Chaffin, Karl W Thomas

Open access · goldAbstract 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 49 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
49citing papers in PubMed, 1 pooled it
14.6field-weighted citation impact, top 1% 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

49 citing papers in PubMed, 1 synthesis or guideline pooled it, 68 citations in OpenAlex.

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  6. Diagnostic Value of End-Tidal Carbon Dioxide Combined With Lactate for Early Detection of Sepsis in Prehospital Patients: A Prospective Cohort Study.Medical science monitor : international medical journal of experimental and clinical research · 2026
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Adam R SchertzDepartment of Internal Medicine, Atrium Health Wake Forest Baptist, Winston-Salem, North Carolina.
Kristin M LenoirDepartment of Biostatistics and Data Science, Division of Public Health Science, Atrium Health Wake Forest Baptist, Winston-Salem, North Carolina.
Alain G BertoniDepartment of Internal Medicine, Atrium Health Wake Forest Baptist, Winston-Salem, North Carolina.
Beverly J LevineSocial Sciences and Health Policy, Wake Forest University School of Medicine, Winston-Salem, North Carolina.
Morgana Mongraw-ChaffinDepartment of Epidemiology and Prevention, Atrium Health Wake Forest Baptist Winston-Salem, North Carolina.
Karl W ThomasDepartment of Internal Medicine, Atrium Health Wake Forest Baptist, Winston-Salem, North Carolina.
Atrium Health Wake Forest Baptist · USWake Forest University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: The Sepsis Prediction Model (SPM) is a proprietary decision support tool created by Epic Systems; it generates a predicting sepsis score (PSS). The model has not undergone validation against existing sepsis prediction tools, such as Systemic Inflammatory Response Syndrome (SIRS), Sequential Organ Failure Assessment (SOFA), or quick Sepsis-Related Organ Failure Asessement (qSOFA). Objective: To assess the validity and timeliness of the SPM compared with SIRS, qSOFA, and SOFA. Design, Setting, and Participants: This retrospective cohort study included all adults admitted to 5 acute care hospitals in a single US health system between June 5, 2019, and December 31, 2020. Data analysis was conducted from March 2021 to February 2023. Main Outcomes and Measures: A sepsis event was defined as receipt of 4 or more days of antimicrobials, blood cultures collected within ±48 hours of initial antimicrobial, and at least 1 organ dysfunction as defined by the organ dysfunction criteria optimized for the electronic health record (eSOFA). Time zero was defined as 15 minutes prior to qualifying antimicrobial or blood culture order. Results: Of 60 507 total admissions, 1663 (2.7%) met sepsis criteria, with 1324 electronic health record-confirmed sepsis (699 [52.8%] male patients; 298 [22.5%] Black patients; 46 [3.5%] Hispanic/Latinx patients; 945 [71.4%] White patients), 339 COVID-19 sepsis (183 [54.0%] male patients; 98 [28.9%] Black patients; 36 [10.6%] Hispanic/Latinx patients; and 189 [55.8%] White patients), and 58 844 (97.3%; 26 632 [45.2%] male patients; 12 698 [21.6%] Black patients; 3367 [5.7%] Hispanic/Latinx patients; 40 491 White patients) did not meet sepsis criteria. The median (IQR) age was 63 (51 to 73) years for electronic health record-confirmed sepsis, 69 (60 to 77) years for COVID-19 sepsis, and 60 (42 to 72) years for nonsepsis admissions. Within the vendor recommended threshold PSS range of 5 to 8, PSS of 8 or greater had the highest balanced accuracy for classifying a sepsis admission at 0.79 (95% CI, 0.78 to 0.80). Change in SOFA score of 2 or more had the highest sensitivity, at 0.97 (95% CI, 0.97 to 0.98). At a PSS of 8 or greater, median (IQR) time to score positivity from time zero was 68.00 (6.75 to 605.75) minutes. For SIRS, qSOFA, and SOFA, median (IQR) time to score positivity was 7.00 (-105.00 to 08.00) minutes, 74.00 (-22.25 to 599.25) minutes, and 28.00 (-108.50 to 134.00) minutes, respectively. Conclusions and Relevance: In this cohort study of hospital admissions, balanced accuracy of the SPM outperformed other models at higher threshold PSS; however, application of the SPM in a clinical setting was limited by poor timeliness as a sepsis screening tool as compared to SIRS and SOFA.

Indexed as

COVID-19SepsisAdultAgedCohort StudiesFemaleHumansMaleMiddle AgedMultiple Organ FailureOrgan Dysfunction ScoresRetrospective StudiesSystemic Inflammatory Response Syndrome

Identifiers

PMID37624600
PMCPMC10457723
OpenAlexW4386153355

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.