MétaCan
Menu
Back to cohort
Record W4416111162 · doi:10.62675/2965-2774.20250124

Incidence of late-onset hyperlactatemia and association with clinical outcomes in intensive care patients

2025· review· en· W4416111162 on OpenAlexaboutno aff
Aashish Kumar, Andrew G. Turner, Kevin B. Laupland, Mahesh Ramanan

Bibliographic record

VenueCritical Care Science · 2025
Typereview
Languageen
FieldMedicine
TopicAdrenal Hormones and Disorders
Canadian institutionsnot available
FundersQueensland Health
KeywordsHyperlactatemiaIncidence (geometry)Intensive careAssociation (psychology)MEDLINEIntensive care unit

Abstract

fetched live from OpenAlex

OBJECTIVE: To perform a systematic literature review to summarise current evidence of the incidence and clinical impact of late-onset hyperlactatemia in intensive care patients about case-fatality and morbidity. METHODS: MEDLINE, EMBASE, and ClinicalTrials.gov were searched using medical subject headings from database inception to 27 November 2024. Before the search, the protocol was registered on the International Prospective Register of Systematic Reviews (PROSPERO). Two independent reviewers screened the search results, and studies were included if they were original research that assessed late-onset hyperlactatemia in critically ill patients. Risk of bias was assessed using the Newcastle-Ottawa Scale, and the data were analysed using a descriptive approach without meta-analysis. RESULTS: Of the 10,388 screened studies, 6 were included in the final manuscript, 5 retrospective and 1 prospective. All were assessed as good quality studies. Five were cardiac surgical patients, and one was general intensive care patients. All six studies reported the incidence of late-onset hyperlactatemia, which ranged from 8.5 to 70.8%. Two studies reported increased intensive care unit and/or hospital case-fatality with late-onset hyperlactatemia; however, small absolute numbers limited the interpretability. CONCLUSION: The limited data regarding late-onset hyperlactatemia make it difficult to draw significant conclusions regarding the relationship to clinical outcomes. However, the few available studies suggest that it is a common finding and highlight the need for further research to assess the underlying aetiologies and association with clinical outcomes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.018
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.376
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.037
GPT teacher head0.433
Teacher spread0.396 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueCritical Care ScienceSame topicAdrenal Hormones and DisordersFrench-language works237,207