Evidence map›Paper›PMID 41990073›Full record

ArticlePloS one2026

Increased serum albumin corrected anion gap levels are associated with poor prognosis in sepsis-induced coagulopathy patients.

ZhenHong Jiang, ShiJin Lv, ZengYan Fu, GuoHu Zhang

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Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

ZhenHong JiangDepartment of Emergency, The Affiliated Hospital of HangZhou Normal University, HangZhou, Zhejiang, China.
ShiJin LvDepartment of Emergency, The Affiliated Hospital of HangZhou Normal University, HangZhou, Zhejiang, China.
ZengYan FuDepartment of Emergency, The Affiliated Hospital of HangZhou Normal University, HangZhou, Zhejiang, China.
GuoHu ZhangDepartment of Emergency, The Affiliated Hospital of HangZhou Normal University, HangZhou, Zhejiang, China.ORCID https://orcid.org/0009-0007-5371-7987

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSepsis-induced coagulopathy (SIC) is associated with high mortality, and acid-base disturbances are common in critically ill patients with this condition. The anion gap (AG) is affected by serum albumin levels, suggesting that the albumin-corrected anion gap (ACAG) may serve as a more accurate prognostic marker. However, the relationship between ACAG and outcomes in SIC remains unclear.

methodsThis retrospective cohort study utilized data from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database (2008-2019). Adult patients (≥18 years) diagnosed with SIC within 24 hours of ICU admission were enrolled. SIC was defined according to the International Society on Thrombosis and Haemostasis (ISTH) criteria combined with Sequential Organ Failure Assessment (SOFA) scores. ACAG was calculated as: ACAG = AG + 2.5 × (4.4 - Albumin [g/dL]). The optimal cutoff value (17.7 mmol/L) was determined using X-tile software. The primary outcome was in-hospital 30-day all-cause mortality. Time-dependent Cox proportional hazards models, Kaplan-Meier (KM) analysis, and receiver operating characteristic (ROC) curves were performed. Subgroup and interaction analyses were conducted to assess effect modification by malignancy status.

resultsA total of 3,846 patients were included (mean age 64.8 years; 38.4% female). Non-survivors exhibited significantly higher ACAG levels than survivors (median [IQR]: 21.4 [18.5-24.8] vs. 17.6 [15.2-20.3] mmol/L, P < 0.001). KM analysis showed that high ACAG (≥17.7 mmol/L) was associated with significantly lower in-hospital 30-day survival (log-rank P < 0.001). In the time-dependent Cox model (adjusted for SOFA, SAPS II, and lactate), high ACAG was independently associated with increased mortality (HR = 3.04, 95% CI: 1.88-4.91, P < 0.001). ACAG demonstrated superior discrimination compared to uncorrected AG (AUC: 0.633 vs. 0.620, DeLong test P < 0.001). Notably, a significant interaction was observed between ACAG and malignancy (P for interaction < 0.001), with ACAG showing stronger predictive value in non-malignant patients (HR = 3.60, P < 0.001) than in those with cancer (HR = 1.59, P = 0.477).

conclusionsElevated ACAG is independently associated with increased in-hospital 30-day mortality in SIC patients and outperforms uncorrected AG. Its calculation requires no additional cost or testing, making it a practical bedside risk stratification tool, particularly for non-malignant patients.

Indexed as

Acid-Base EquilibriumBlood Coagulation DisordersSepsisSerum AlbuminAgedBiomarkersFemaleHumansIntensive Care UnitsKaplan-Meier EstimateMaleMiddle AgedPrognosisProportional Hazards ModelsRetrospective StudiesROC CurveBiomarkersSerum Albumin

Identifiers

PMID41990073
PMCPMC13086298

What Socratic holds

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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 Socratic graph.