ArticleCureus2026
Decoding Thrombocytopenia in Dengue: Platelet Indices Define Mechanistic Phenotypes and Predict Bleeding Risk.
Article in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThrombocytopenia is a characteristic of dengue infection; however, the underlying mechanisms of these phenotypes remain underexplored clinically. Platelet indices may serve as a swift and accessible method for mechanistic distinction and risk assessment.
objectiveThe objective of this study was to evaluate platelet indices for mechanistic categorization of thrombocytopenia phenotypes in dengue patients, assess their association with bleeding risk, determine their diagnostic performance for bleeding prediction, and develop a preliminary Dengue Bleeding Risk Score (DBRS) for risk stratification.
methodA case-control study included 334 dengue cases and 101 controls. We examined platelet count (PLT), plateletcrit (PCT), immature platelet fraction (IPF), mean platelet component (MPC), mean platelet volume (MPV), platelet distribution width (PDW), platelet large cell ratio (PLCR), platelet large cell count (PLCC), and coagulation parameters. Thrombocytopenia was classified into four phenotypes: hyperdestructive, inadequate response, hypoproductive, and lazy-suppressed, based on PLT and IPF. Platelet indices, coagulation parameters, and clinical outcomes were analyzed. Logistic regression and receiver operating characteristic (ROC) curve analyses were performed to evaluate bleeding risk.
resultsThrombocytopenia was present in 82.9% of patients, with inadequate response being the most common phenotype (55.7%). A significant shift toward the hyperdestructive phenotype was observed as disease severity increased (p < 0.001). Bleeding differed significantly across phenotypes, with the highest frequency in the hyperdestructive group (57.1%). In unadjusted analysis, this phenotype was strongly associated with bleeding (OR 13.25, 95% CI 4.11-42.71, p < 0.001); however, this association was not independent after adjustment for disease severity (OR 2.83, 95% CI 0.59-13.60, p = 0.194). Severe dengue remained the strongest predictor of bleeding (adjusted OR 41.83, 95% CI 14.41-121.46, p < 0.001). IPF and MPC demonstrated moderate performance in predicting bleeding (area under the curve (AUC) 0.723 and 0.718, respectively).
conclusionThrombocytopenia in dengue is a heterogeneous, mechanism-based condition characterized by diverse phenotypes; however, bleeding risk is primarily determined by disease severity rather than phenotype alone. The incorporation of platelet indices into a composite model, such as the DBRS, may provide a more comprehensive approach to risk stratification than platelet count alone, although further validation in independent cohorts is required.
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.