Evidence map›Paper›PMID 42304250›Full record

ArticleBMC infectious diseases2026

Clinical and laboratory characteristics associated with liver failure in hospitalized dengue patients: insights from a non-endemic region.

Si Yu Zhao, Ya Peng Zhang, Zhuan Zhou, Yong Wu, Jin Wei Hu

Abstract read
In one paragraph

Article in BMC infectious diseases, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Si Yu ZhaoDepartment of Laboratory Medicine, The First Hospital of Changsha (The Affiliated Changsha Hospital of Xiangya School of Medicine, Central South University), Changsha, Hunan, China.
Ya Peng ZhangDepartment of Laboratory Medicine, The First Hospital of Changsha (The Affiliated Changsha Hospital of Xiangya School of Medicine, Central South University), Changsha, Hunan, China.
Zhuan ZhouDepartment of Laboratory Medicine, The First Hospital of Changsha (The Affiliated Changsha Hospital of Xiangya School of Medicine, Central South University), Changsha, Hunan, China.
Yong WuDepartment of Laboratory Medicine, The First Hospital of Changsha (The Affiliated Changsha Hospital of Xiangya School of Medicine, Central South University), Changsha, Hunan, China.
Jin Wei HuDepartment of Laboratory Medicine, The First Hospital of Changsha (The Affiliated Changsha Hospital of Xiangya School of Medicine, Central South University), Changsha, Hunan, China. cshujinwei@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDengue fever is an emerging public health issue expanding into non-endemic regions like Changsha, China. Liver involvement is a critical complication, and early identification of patients at risk of liver failure remains challenging. This study aimed to characterize hospitalized dengue patients, identify routine laboratory parameters significantly associated with liver failure, and utilize a machine learning model to corroborate the importance of these parameters in this non-endemic setting.

methodsA retrospective chart review was conducted on 86 laboratory-confirmed dengue patients hospitalized at the First Hospital of Changsha between 2023 and 2024. Routine demographic and laboratory data were collected. Statistical analyses were performed to identify parameters associated with liver failure within this cohort. Separately, a random forest model was developed using an independent dataset of dengue patients and healthy controls to rank feature importance for distinguishing dengue from a healthy baseline.

resultsAmong 86 dengue patients, mean age was 38.8 years, with 48.8% male. Cases peaked in summer and autumn. Common abnormalities included leukopenia (83.7%), thrombocytopenia (47.7%), elevated ALT (52.3%), AST (48.8%), and LDH (46.9%). After excluding patients with pre-existing liver disease or co-infections, 79 patients were analyzed for liver failure risk factors. Compared with patients without liver failure (n = 40), those with liver failure (n = 39) had significantly lower platelet counts (P = 0.003) and higher ALT (P = 0.005), AST (P = 0.045), and LDH (P = 0.041). A random forest model ranked AST, platelets, and ALT among its top features for distinguishing dengue from healthy status.

conclusionPlatelet count, ALT, AST, and LDH were identified as laboratory parameters associated with dengue-related liver failure in hospitalized patients. A complementary machine learning-based feature importance analysis showed consistent ranking of key variables in an independent dataset. These findings provide potential biomarkers for risk stratification and support future prospective validation studies.

Indexed as

DengueLiver FailureAdultChinaFemaleHospitalizationHumansMachine LearningMaleMiddle AgedRandom ForestRetrospective StudiesRisk FactorsYoung AdultDengue feverLaboratory parametersLiver failureNon-endemic regionRandom forest

Identifiers

PMID42304250
PMCPMC13449496

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.