Novel insights into immune dysregulation and cytokine signatures in intensive care settings: bridging IL-6, IL-10, TNF-α to endothelial, hepatic, and hematological dysfunction in severe dengue, a schematic meta-analysis.
Bibliographic record
Abstract
Background & objective: Severe dengue is a global health concern and immune dysregulation is a key contributor to its pathogenesis. The aim of this schematic review was to review the association of the cytokine biomarkers mainly interleukin-6 (IL-6), interleukin-10 (IL-10) and tumor necrosis factor-alpha (TNF-α) in immune dysregulation among patients suffering from severe dengue. Methodology: The review followed PRISMA 2020 guidelines. The literature was searched from PubMed, Scopus, Web of Science, and Google Scholar up to August 2025. Qualified studies included those which measured IL-6, IL-10 or TNF- α in confirmed dengue patient. Meta-analysis was performed to assess standardized mean differences (SMDs) for key cytokines. The risk of bias was determined using Newcastle-Ottawa Scale and the GRADE approach was applied for certainty of evidence. Results: Higher levels were observed, of IL-6 and IL-10 in severe dengue, and TNF-α with late complications in this study. Meta-analysis correlated high levels of cytokines with severe dengue IL-6 (SMD = 16.79, 95% CI = -15.25-48.84), IL-10 (SMD = 0.13, 95%CI = -0.37-0.63) and TNF-α (SMD = 0.53, 95% CI = 0.25-0.82). The evidence confidence was moderate and high by IL-6 and IL-10 and high in TNF-α respectively. Conclusion: The levels of IL-6 and IL-10 were significantly high in severe dengue cases, but heterogeneity across studies reduced the prognostic integrity. TNF-α emerged as a potent indicator of mild and severe dengue. To establish the clinical uses of these biomarkers as a risk-stratifying tool, standardized, multicentric studies are needed to validate these findings. Abbreviations: DF: dengue fever, DHF: dengue hemorrhagic fever, DSS: dengue shock syndrome, IL-6: Interleukin-6, IL-10: Interleukin-10, SMD: standardized mean differences, TNF-α: tumor necrosis factor-alpha Keywords: Dengue Hemorrhagic Fever (DHF), Cytokine Storm, Biomarkers, Cytokines, IL-6, IL-10, TNF-α Citation: Bukhari AAS, Devi D, Minhas M, Noureen A, Javed H, Zaidi SIA, Khaliq H. Novel insights into immune dysregulation and cytokine signatures in intensive care settings: bridging IL-6, IL-10, TNF-α to endothelial, hepatic, and hematological dysfunction in severe dengue, a schematic meta-analysis. Anaesth. pain intensive care 2025;29(8):1022-1031. DOI: 10.35975/apic.v29i8.3039 Received: October 16, 2025; Revised: October 18, 2025; Accepted: October 18, 2025
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.022 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".