Evidence map›Paper›PMID 33301017›Full record

ArticleJAMA network open2020

Assessment of Machine Learning to Estimate the Individual Treatment Effect of Corticosteroids in Septic Shock.

Romain Pirracchio, Alan Hubbard, Charles L Sprung, Sylvie Chevret, Djillali Annane, Rapid Recognition of Corticosteroid Resistant or Sensitive Sepsis (RECORDS) Collaborators

Open access · goldAbstract readValidation Study
In one paragraph

Article in JAMA network open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 3 pooled it
4.5field-weighted citation impact, top 4% 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

35 citing papers in PubMed, 3 syntheses or guidelines pooled it, 61 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Guideline
  4. Trial
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  8. What place for pragmatic RCTs in intensive care?Critical care (London, England) · 2026
    Review
  9. Article
  10. Review
  11. Article
  12. Advancing Precision Nutrition Through Multimodal Data and Artificial Intelligence.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  13. Article
  14. Article
  15. Article
  16. Corticosteroids in sepsis.Journal of intensive medicine · 2025
    Review
  17. Article
  18. Article
  19. Review
  20. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 5 institutions in 3 countries.

Romain PirracchioDepartment of Anesthesia and Perioperative Medicine, Zuckerberg San Francisco general Hospital and Trauma Center, University of California, San Francisco.
Alan HubbardDivision of Biostatistics, School of Public Health, University of California, Berkeley.
Charles L SprungDepartment of Anesthesiology, Critical Care Medicine and Pain, Hadassah Hebrew University Medical Center, Jerusalem, Israel.
Sylvie ChevretDepartment of Biostatistics and Medical Informatics, Institut national de la santé et de la recherche médicale Unite Mixte de Recherche 1153, Hospital Saint Louis, University of Paris, Paris, France.
Djillali AnnaneSaclay and Paris Seine Nord Endeavour to Personalize Interventions for Sepsis, Rapid Recognition of Corticosteroid Resistant or Sensitive Sepsis, Department of Intensive Care, Hôpital Raymond Poincaré Groupes Hospitalo-Universitaires Assistance Publique-Hôpitaux de Paris, Université Paris Saclay, Laboratory of Infection and Inflammation, School of Medicine Simone Veil, University Versailles Saint Quentin, University Paris Saclay, Institut national de la santé et de la recherche médicale, Garches, France.
Rapid Recognition of Corticosteroid Resistant or Sensitive Sepsis (RECORDS) Collaborators
Hadassah Medical Center · ILUniversité Paris Cité · FRUniversité Paris-Saclay · FRUniversity of California, Berkeley · USUniversity of California, San Francisco · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: The survival benefit of corticosteroids in septic shock remains uncertain. Objective: To estimate the individual treatment effect (ITE) of corticosteroids in adults with septic shock in intensive care units using machine learning and to evaluate the net benefit of corticosteroids when the decision to treat is based on the individual estimated absolute treatment effect. Design, Setting, and Participants: This cohort study used individual patient data from 4 trials on steroid supplementation in adults with septic shock as a training cohort to model the ITE using an ensemble machine learning approach. Data from a double-blinded, placebo-controlled randomized clinical trial comparing hydrocortisone with placebo were used for external validation. Data analysis was conducted from September 2019 to February 2020. Exposures: Intravenous hydrocortisone 50 mg dose every 6 hours for 5 to 7 days with or without enteral 50 μg of fludrocortisone daily for 7 days. The control was either the placebo or usual care. Main Outcomes and Measures: All-cause 90-day mortality. Results: A total of 2548 participants were included in the development cohort, with median (interquartile range [IQR]) age of 66 (55-76) years and 1656 (65.0%) men. The median (IQR) Simplified Acute Physiology Score (SAPS II) was 55 [42-69], and median (IQR) Sepsis-related Organ Failure Assessment score on day 1 was 11 (9-13). The crude pooled relative risk (RR) of death at 90 days was 0.89 (95% CI, 0.83 to 0.96) in favor of corticosteroids. According to the optimal individual model, the estimated median absolute risk reduction was of 2.90% (95% CI, 2.79% to 3.01%). In the external validation cohort of 75 patients, the area under the curve of the optimal individual model was 0.77 (95% CI, 0.59 to 0.92). For any number willing to treat (NWT; defined as the acceptable number of people to treat to avoid 1 additional outcome considering the risk of harm associated with the treatment) less than 25, the net benefit of treating all patients vs treating nobody was negative. When the NWT was 25, the net benefit was 0.01 for the treat all with hydrocortisone strategy, -0.01 for treat all with hydrocortisone and fludrocortisone strategy, 0.06 for the treat by SAPS II strategy, and 0.31 for the treat by optimal individual model strategy. The net benefit of the SAPS II and the optimal individual model treatment strategies converged to zero for a smaller number willing to treat, but the individual model was consistently superior than model based on the SAPS II score. Conclusions and Relevance: These findings suggest that an individualized treatment strategy to decide which patient with septic shock to treat with corticosteroids yielded positive net benefit regardless of potential corticosteroid-associated side effects.

Indexed as

Machine LearningShock, SepticAgedClinical Decision-MakingCritical CareFemaleFludrocortisoneGlucocorticoidsHumansHydrocortisoneIntensive Care UnitsMaleOrgan Dysfunction ScoresPrognosisRandomized Controlled Trials as TopicRisk AdjustmentFludrocortisoneGlucocorticoidsHydrocortisone

Identifiers

PMID33301017
PMCPMC7729430
OpenAlexW3112047593

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.