Evidence map›Paper›PMID 40924910›Full record

ArticleCritical care explorations2025

Immune Response Subphenotyping to Predict Mortality in Sepsis: A Prospective Study in Resource-Limited Setting.

Velma Herwanto, Robert Sinto, Leonard Nainggolan, Adityo Susilo, Evy Yunihastuti, Ceva Wicaksono Pitoyo, Hamzah Shatri, Khie Chen Lie

Abstract read
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Article in Critical care explorations, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Velma HerwantoDivision of Internal Medicine, Faculty of Medicine Universitas Tarumanagara, Jakarta, Indonesia; Siloam Hospitals Kebon Jeruk, Jakarta, Indonesia.ORCID 0000-0003-3644-3156
Robert SintoDivision of Tropical Medicine and Infectious Diseases, Department of Internal Medicine, Dr. Cipto Mangunkusumo National General Hospital, Faculty of Medicine Universitas Indonesia, Jakarta, Indonesia.
Leonard NainggolanDivision of Tropical Medicine and Infectious Diseases, Department of Internal Medicine, Dr. Cipto Mangunkusumo National General Hospital, Faculty of Medicine Universitas Indonesia, Jakarta, Indonesia.
Adityo SusiloDivision of Tropical Medicine and Infectious Diseases, Department of Internal Medicine, Dr. Cipto Mangunkusumo National General Hospital, Faculty of Medicine Universitas Indonesia, Jakarta, Indonesia.
Evy YunihastutiDivision of Allergy and Clinical Immunology, Department of Internal Medicine, Dr. Cipto Mangunkusumo National General Hospital, Faculty of Medicine Universitas Indonesia, Jakarta, Indonesia.
Ceva Wicaksono PitoyoDivision of Respiratory and Critical Care, Department of Internal Medicine, Dr. Cipto Mangunkusumo National General Hospital, Faculty of Medicine Universitas Indonesia, Jakarta, Indonesia.
Hamzah ShatriDivision of Psychosomatic and Palliative, Department of Internal Medicine, Dr. Cipto Mangunkusumo National General Hospital, Faculty of Medicine Universitas Indonesia, Jakarta, Indonesia.
Khie Chen LieDivision of Tropical Medicine and Infectious Diseases, Department of Internal Medicine, Dr. Cipto Mangunkusumo National General Hospital, Faculty of Medicine Universitas Indonesia, Jakarta, Indonesia.

Funding

Universitas Tarumanagara 0142-Int-KLPPM/UNTAR/III/2024
6 · The paper itself

Abstract

importanceSepsis remains a leading cause of death in infectious cases. The heterogeneity of immune responses is a major challenge in the management and prognostication of patients with sepsis. Identifying distinct immune response subphenotypes using parsimonious classifiers may improve outcome prediction, particularly in resource-limited settings.

objectivesThis study aimed to evaluate whether classification of the immune response can serve as a predictor of mortality. DESIGN, SETTING, AND

participantsThis prospective cohort study was conducted in the emergency department, inpatient wards, and ICU of a tertiary hospital. Adult patients diagnosed with sepsis within the previous 24 hours were included. Exclusion criteria were history of RBC transfusion, major thalassemia, decompensated cirrhosis, hematologic malignancy, or use of immunosuppressive or chronic corticosteroid therapy. Demographic, clinical, and laboratory data-including serum ferritin and monocyte human leukocyte antigen-DR/Human Leukocyte Antigen-DR) (mHLA-DR) levels-were collected. MAIN OUTCOMES AND MEASURES: Subjects were classified into the following immune subphenotypes: macrophage activation-like syndrome (MALS) (if ferritin > 4420 ng/mL), immunoparalysis (if mHLA-DR < 10,000 receptors/cell and ferritin ≤ 4420 ng/mL), and unclassified (if they did not meet the criteria for either MALS or immunoparalysis). The primary outcome was in-hospital mortality.

resultsOf the 200 subjects recruited, 54 (27%) were classified into the MALS group, 19 (9.5%) into the immunoparalysis group, and the remainder into the unclassified group. The in-hospital mortality rates for the MALS, immune paralysis, and unclassified groups were 83.3%, 68.4%, and 51.1%, respectively. The proportional hazards assumption was met between the MALS and unclassified groups (crude hazard ratio [HR] 2.3; 95% CI, 1.56-3.35) but not between the immunoparalysis and unclassified groups (crude HR 1.4; 95% CI, 0.76-2.50). After adjusting for confounding variables, MALS's adjusted HR was 1.7 (95% CI, 1.13-2.49; p = 0.01). CONCLUSIONS AND RELEVANCE: The MALS subphenotype is an independent predictor of in-hospital mortality in sepsis.

Indexed as

SepsisAdultAgedFemaleFerritinsHLA-DR AntigensHospital MortalityHumansIntensive Care UnitsMaleMiddle AgedPrognosisProspective StudiesResource-Limited SettingsFerritinsHLA-DR Antigensimmunoparalysismacrophage activation-like syndromemortalitysepsis

Identifiers

PMID40924910
PMCPMC12422772

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.