Evidence map›Paper›PMID 41429875›Full record

ArticleNPJ digital medicine2025

Prospective evaluation of speech as a digital biomarker for covert hepatic encephalopathy.

Jakub Gazda, Juan Carlos García-Pagán, Sylvia Drazilova, Peter Drotar, Mate Hires, Matej Gazda, Martin Janicko, Anna Baiges, Peter Jarcuska

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in NPJ digital medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Reducing the Risk of Overt Hepatic Encephalopathy Recurrence: A Narrative Review.Journal of clinical and translational hepatology · 2026
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Jakub Gazda2nd Department of Internal Medicine, Pavol Jozef Safarik University and L Pasteur University in Kosice, Trieda SNP 1, 040 11, Kosice, Slovakia.
Juan Carlos García-PagánBarcelona Hepatic Hemodynamic Laboratory, Liver Unit, Hospital Clínic Barcelona, Institut de Investigacions Biomediques August Pi i Sunyer (IDIBAPS). CIBEREHD (Centro de Investigacion Biomedica en Red Enfermedades Hepaticas y Digestivas). Health Care Provider of the European Reference Network on Rare Liver Disorders (ERN RARE-Liver). Departament de Medicina i Ciencies de la Salut. Universidad de Barcelona, Barcelona, Spain.
Sylvia Drazilova2nd Department of Internal Medicine, Pavol Jozef Safarik University and L Pasteur University in Kosice, Trieda SNP 1, 040 11, Kosice, Slovakia.
Peter DrotarIntelligent Information Systems Lab, Technical University of Kosice, Letna 9, 042 00, Kosice, Slovakia.
Mate HiresIntelligent Information Systems Lab, Technical University of Kosice, Letna 9, 042 00, Kosice, Slovakia.
Matej GazdaIntelligent Information Systems Lab, Technical University of Kosice, Letna 9, 042 00, Kosice, Slovakia.
Martin Janicko2nd Department of Internal Medicine, Pavol Jozef Safarik University and L Pasteur University in Kosice, Trieda SNP 1, 040 11, Kosice, Slovakia. martin.janicko@upjs.sk.ORCID http://orcid.org/0000-0002-3329-3968
Anna Baiges *Barcelona Hepatic Hemodynamic Laboratory, Liver Unit, Hospital Clínic Barcelona, Institut de Investigacions Biomediques August Pi i Sunyer (IDIBAPS). CIBEREHD (Centro de Investigacion Biomedica en Red Enfermedades Hepaticas y Digestivas). Health Care Provider of the European Reference Network on Rare Liver Disorders (ERN RARE-Liver). Departament de Medicina i Ciencies de la Salut. Universidad de Barcelona, Barcelona, Spain.
Peter Jarcuska *2nd Department of Internal Medicine, Pavol Jozef Safarik University and L Pasteur University in Kosice, Trieda SNP 1, 040 11, Kosice, Slovakia.

Funding

VAIA No. 09I05-03-V05-00044
6 · The paper itself

Abstract

Covert hepatic encephalopathy is a highly prevalent complication of liver failure or portosystemic shunting. However, the current diagnostic methods have not been widely adopted in routine clinical practice due to their time-consuming or technically complex nature. This study aimed to develop and evaluate a clinically feasible machine learning model capable of detecting covert hepatic encephalopathy using features extracted from sustained vowel phonation recordings. The XGBoost model achieved the highest AUROC of 81.20 (95% CI 73.03-89.73) and showed reasonable calibration across the full spectrum of predicted probabilities (Hosmer-Lemeshow p = 0.66). The most influential features indicated that patients with covert hepatic encephalopathy tended to have reduced variation in volume, maintaining more constant and harsher vocal quality.

Identifiers

PMID41429875
PMCPMC12748680

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Registered trials

None linked

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.