Evidence map›Paper›PMID 33435876›Full record

ArticleBMC anesthesiology2021

Association between normalized lactate load and mortality in patients with septic shock: an analysis of the MIMIC-III database.

Han Chen, Shu-Rong Gong, Rong-Guo Yu

Abstract read
In one paragraph

Article in BMC anesthesiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

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21citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

21 citing papers in PubMed.

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  6. Predictive Value of Normalized Lactate Load for Patients with Acute Type A Aortic Dissection: Based on the MIMIC-IV Database.Annals of thoracic and cardiovascular surgery : official journal of the Association of Thoracic and Cardiovascular Surgeons of Asia · 2025
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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Han ChenSurgical Intensive Care Unit, Fujian Provincial Clinical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou, China.
Shu-Rong GongSurgical Intensive Care Unit, Fujian Provincial Clinical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou, China.
Rong-Guo YuSurgical Intensive Care Unit, Fujian Provincial Clinical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou, China. garyyrg@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAn index of dynamic lactate change that incorporates both the magnitude of change and the time interval of such change, termed "normalized lactate load," may reflect the hypoxic burden of septic shock. We aimed to evaluate the association between normalized lactate load and 28-day mortality in adult septic shock patients.

methodsPatients with septic shock were identified from the Medical Information Mart for Intensive Care (MIMIC)-III database. Lactate load was defined as the sum of the area under the curve (AUC) of serial lactate levels using the trapezoidal rule, and normalized lactate load was defined as the lactate load divided by time. Receiver-operating characteristic curves were constructed to determine the performance of initial lactate, maximum lactate and normalized lactate load in predicting 28-day mortality.

resultsA total of 1371 septic shock patients were included, and the 28-day mortality was 39.8%. Non-survivors had significantly higher initial lactate (means ± standard deviations: 3.9 ± 2.9 vs. 2.8 ± 1.7 mmol/L), maximum lactate (5.8 ± 3.8 vs. 4.3 ± 2.2 mmol/L), lactate load (94.3 ± 71.8 vs. 61.1 ± 36.4 mmol·hr./L) and normalized lactate load (3.9 ± 3.0 vs. 2.5 ± 1.5 mmol/L, all p <  0.001). The AUCs of initial lactate, maximum lactate and normalized lactate load were 0.623 (95% confidence interval: 0.596-0.648, with a cut-off value of 4.4 mmol/L), 0.606 (0.580-0.632, with a cut-off value of 2.6 mmol/L) and 0.681 (0.656-0.706, with a cut-off value of 2.6 mmol/L), respectively. The AUC of normalized lactate load was significantly greater than both initial lactate and maximum lactate (all p <  0.001). In the multivariate logistic regression model, normalized lactate load was identified as an independent risk factor for 28-day mortality.

conclusionsNormalized lactate load is an independent risk factor for 28-day mortality in adult septic shock patients. Normalized lactate load had better accuracy than both initial and maximum lactate in determining the prognosis of septic shock patients.

Indexed as

AgedAge FactorsDatabases, FactualFemaleHumansLactic AcidMaleShock, SepticLactic AcidLactateMIMIC-IIIMortalitySeptic shock

Identifiers

PMID33435876
PMCPMC7802303

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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.