Evidence map›Paper›PMID 42116308›Full record

Observational studyMedicine2026

Do pleural fluid pH and lactate improve classification beyond Light's criteria?: A single-center retrospective study.

Berrin Zinnet Eraslan, Elif Yilmaz, Sümeyye Kodalak Cengiz, Sevda Cömert

Abstract readObservational Study
In one paragraph

Observational study in Medicine, 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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0citing 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

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors.

Berrin Zinnet EraslanDepartment of Pulmonology, Kartal Dr. Lütfi Kirdar City Hospital, Istanbul, Türkiye.ORCID 0000-0002-2425-6903
Elif Yilmaz
Sümeyye Kodalak Cengiz
Sevda Cömert

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accurate differentiation between transudative and exudative pleural effusions is essential for determining the underlying etiology and guiding management. Although Light's criteria remain the standard diagnostic approach, their performance may be limited in borderline cases. Biochemical markers such as pleural fluid pH and lactate have been proposed as adjunct tools, yet the extent to which they provide additional diagnostic improvement beyond Light's criteria remains unclear. This single-center retrospective study specifically evaluated whether adding pleural fluid pH and lactate to Light's criteria improves the ability to distinguish transudative from exudative pleural effusions, quantifying the additional diagnostic value of these markers. We retrospectively analyzed 281 patients who underwent diagnostic thoracentesis between November 2020 and March 2024. Receiver operating characteristic-derived cutoff values and corresponding area under the curve (AUC)s for pH and lactate were generated and assessed within the same cohort. Multivariable logistic regression models incorporating Light's criteria alone and in combination with pH and/or lactate were constructed to assess incremental discrimination (ΔAUC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI). Of the 281 patients, 62 (22.1%) had transudative and 219 (77.9%) had exudative effusions. Pleural fluid pH ≤ 7.44 showed an AUC of 0.767 (95% CI, 0.696-0.839), sensitivity 71.4%, and specificity 70.2%. Lactate ≥ 2.05 mmol/L yielded an AUC of 0.701 (95% CI, 0.627-0.775), sensitivity 61.7%, and specificity 63.2%. Adding pH to Light's criteria increased diagnostic accuracy (Model-2 AUC 0.985; ΔAUC + 0.010; NRI 0.904; IDI 0.035). Lactate also improved discrimination, though to a lesser extent (Model-3 AUC 0.982; ΔAUC + 0.007; NRI 0.607; IDI 0.025). Incorporating both biomarkers provided the highest incremental metrics (AUC 0.986; ΔAUC + 0.011; IDI 0.053), demonstrating a modest additive benefit across models. Pleural fluid pH and lactate, when added to Light's criteria, provide distinct yet modest incremental gains in diagnostic performance. These findings clarify their potential as an adjunct, though further external validation is necessary before routine clinical application.

Indexed as

Exudates and TransudatesLactic AcidPleural EffusionAgedBiomarkersDiagnosis, DifferentialFemaleHumansHydrogen-Ion ConcentrationLogistic ModelsMaleMiddle AgedRetrospective StudiesROC CurveThoracentesisBiomarkersLactic Acidexudatelactatelight’s criteriapHpleural effusionROC analysistransudate

Identifiers

PMID42116308
PMCPMC13166768

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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.