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Peer-reviewedCC BY 4.0Journal of Translational Medicine

Precision hyperbaric oxygen therapy: a biomarker-driven framework

  • Halimureti Simayijiang1,2
  • Yueling Lin2
  • Tingting Zhong2
  • Zhuo Li3
  • Kun Zhang2
  • Ying Long3
  1. 1South China Hospital, Medical School, Shenzhen University, Shenzhen, P.R. China
  2. 2Yiyuan Longevity Technology (Shenzhen) Co., Ltd, Shenzhen, P.R. China
  3. 3Department of Hyperbaric Oxygen, Shenzhen People’s Hospital, Shenzhen, P.R. China
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Abstract

Background: Hyperbaric oxygen therapy (HBOT) remains limited by insufficient individualization, a lack of biomarker-guided dosing, and heterogeneous clinical outcomes across indications and patient populations. We propose a translational, biomarker-driven framework for treating HBOT as a measurable and titratable intervention. This narrative review presents a conceptual framework rather than a formal systematic review or a clinically validated dosing algorithm.

Methods: Dosing is quantified using pressure–time integral (PTI) and cumulative oxygen exposure. A three-tier biomarker architecture supports decision-making: proximal sensors (redox balance, mitochondrial function, endothelial and microcirculatory responses), mechanistic mediators (inflammation–immunity and senescence), and integrative endpoints (epigenetic clocks, multi-omics, functional outcomes, and patient-reported measures). These signals are proposed for integration into a Composite Response Index (CRI) to support prospective evaluation of real-time monitoring and adaptive titration across treatment cycles and clinical scenarios. Evidence is synthesized narratively across HBOT indications, oxygen-biology mechanisms, safety literature, trial-methodology guidance, and biomarker-practicality considerations.

Results: The framework proposes candidate, prospectively testable rules for dose adjustment, phenotype-based stratification, and biologically aligned monitoring schedules. It supports dual-channel stratification by indication and phenotype, enabling hypothesis-driven “right patient, right dose” strategies, and integrates evidence generation across randomized trials, platform studies, and real-world data using causal inference and Bayesian approaches. These operational rules are intended as framework-level proposals and require prospective validation before routine clinical implementation.

Conclusions: This biomarker-driven strategy operationalizes HBOT as a quantifiable intervention, enabling personalized dosing, improved reproducibility, and more consistent clinical responses, with translational potential across neurorehabilitation, cardiometabolic health, wound care, and healthy ageing. The CRI, PTI-based dose mapping, biomarker thresholds, and titration rules should therefore be interpreted as a de novo implementation framework and prospective validation target, not as clinically validated decision limits.

Supplementary Information: The online version contains supplementary material available at https://doi.org/10.1186/s12967-026-08722-w.

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Cite

BibTeXRIS
BibTeX
@article{simayijiang2026precision,
  title = {{Precision hyperbaric oxygen therapy: a biomarker-driven framework}},
  author = {Halimureti Simayijiang and Yueling Lin and Tingting Zhong and Zhuo Li and Kun Zhang and Ying Long},
  journal = {Journal of Translational Medicine},
  year = {2026},
  month = jul,
  doi = {10.1186/s12967-026-08722-w},
  url = {https://doi.org/10.1186/s12967-026-08722-w},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - Precision hyperbaric oxygen therapy: a biomarker-driven framework
AU  - Halimureti Simayijiang
AU  - Yueling Lin
AU  - Tingting Zhong
AU  - Zhuo Li
AU  - Kun Zhang
AU  - Ying Long
PY  - 2026
DA  - 2026/07/30
JO  - Journal of Translational Medicine
DO  - 10.1186/s12967-026-08722-w
UR  - https://doi.org/10.1186/s12967-026-08722-w
AB  - Background: Hyperbaric oxygen therapy (HBOT) remains limited by insufficient individualization, a lack of biomarker-guided dosing, and heterogeneous clinical outcomes across indications and patient populations. We propose a translational, biomarker-driven framework for treating HBOT as a measurable and titratable intervention. This narrative review presents a conceptual framework rather than a formal systematic review or a clinically validated dosing algorithm.  Methods: Dosing is quantified using pressure–time integral (PTI) and cumulative oxygen exposure. A three-tier biomarker architecture supports decision-making: proximal sensors (redox balance, mitochondrial function, endothelial and microcirculatory responses), mechanistic mediators (inflammation–immunity and senescence), and integrative endpoints (epigenetic clocks, multi-omics, functional outcomes, and patient-reported measures). These signals are proposed for integration into a Composite Response Index (CRI) to support prospective evaluation of real-time monitoring and adaptive titration across treatment cycles and clinical scenarios. Evidence is synthesized narratively across HBOT indications, oxygen-biology mechanisms, safety literature, trial-methodology guidance, and biomarker-practicality considerations.  Results: The framework proposes candidate, prospectively testable rules for dose adjustment, phenotype-based stratification, and biologically aligned monitoring schedules. It supports dual-channel stratification by indication and phenotype, enabling hypothesis-driven “right patient, right dose” strategies, and integrates evidence generation across randomized trials, platform studies, and real-world data using causal inference and Bayesian approaches. These operational rules are intended as framework-level proposals and require prospective validation before routine clinical implementation.  Conclusions: This biomarker-driven strategy operationalizes HBOT as a quantifiable intervention, enabling personalized dosing, improved reproducibility, and more consistent clinical responses, with translational potential across neurorehabilitation, cardiometabolic health, wound care, and healthy ageing. The CRI, PTI-based dose mapping, biomarker thresholds, and titration rules should therefore be interpreted as a de novo implementation framework and prospective validation target, not as clinically validated decision limits.  Supplementary Information: The online version contains supplementary material available at https://doi.org/10.1186/s12967-026-08722-w.
SN  - 1479-5876
ER  -