ArticleFrontiers in medicine2025
Potential source of bias in AI models: lactate measurement in the ICU in sepsis patients as a template.
Article in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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.
Who cites it
3 citing papers in PubMed.
- Artificial Intelligence and Algorithmic Bias in Burn Care: A Literature Review of Ethical Challenges.Journal of burn care & research : official publication of the American Burn Association · 2026Review
- Mechanistic Studies of Lactate in Heart Failure: From Metabolic Biomarker to Therapeutic Target.Reviews in cardiovascular medicine · 2026Review
- What is the ideal glucose range for a patient with sepsis in the ICU? A retrospective analysis of MIMIC-IV.BMJ open · 2026Article
Corrections and comments
- Update of
Authors and funding
14 authors.
Funding
Abstract
Objective: Health inequities may be driven by demographics such as sex, language proficiency, and race-ethnicity. These disparities may manifest through likelihood of testing, which in turn can bias artificial intelligence models. We aimed to evaluate variation in serum lactate measurements in the intensive care unit (ICU) in sepsis. Methods: Utilizing MIMIC-IV (2008-2019), we identified adults fulfilling sepsis-3 criteria. Exclusion criteria were ICU stay < 1-day, unknown race-ethnicity, < 18 years of age, and recurrent ICU-stays. Employing targeted maximum likelihood estimation analysis, we assessed the likelihood of a lactate measurement on day 1. For patients with a measurement on day 1, we evaluated the predictors of subsequent readings. Results: We studied 15,601 patients (19.5% racial-ethnic minority, 42.4% female, and 10.0% limited English proficiency). After adjusting for confounders, Black patients had a slightly higher likelihood of receiving a lactate measurement on day 1 [odds ratio 1.19, 95% confidence interval (CI) 1.06-1.34], but not the other minority groups. Subsequent frequency was similar across race-ethnicities, but women had a lower incidence rate ratio (IRR) 0.94 (95% CI 0.90-0.98). Patients with elective admission and private insurance also had a higher frequency of repeated serum lactate measurements (IRR 1.70, 95% CI 1.61-1.81 and 1.07, 95% CI, 1.02-1.12, respectively). Conclusion: We found no disparities in the likelihood of a lactate measurement among patients with sepsis across demographics, except for a small increase for Black patients, and a reduced frequency for women. Subsequent analyses should account for the variation in biomarker monitoring being present in MIMIC-IV.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.