Hyperbaric oxygen therapy to promote wound healing in severe pancytopenia: a case report
Bibliographic record
Abstract
OBJECTIVE: Wound healing fundamentally requires an intact haematologic profile, and an adequate number and function of leukocytes, erythrocytes and platelets is a precondition for quelling infection and remodelling damaged tissue. Hyperbaric oxygen therapy (HBOT) is an adjunctive management for chronic and complex wounds and, unlike many classical elements of multidisciplinary wound care, its effects are not wholly mediated by these cell lineages. HBOT is known to enhance oxygen delivery to tissues, and support microvascular growth, to facilitate wound healing. HBOT also promotes the mobilisation of endogenous stem cells; however, its use in combination with bone marrow transplantation to augment engraftment is controversial. METHOD: We describe a case report in which HBOT was successfully applied as part of ongoing adjuvant treatment for a complex sacral wound, in the context of myelodysplastic syndrome and aplastic anaemia, to facilitate allogenic bone marrow transplantation and subsequent recovery. RESULTS: After ongoing wound deterioration despite conventional therapy and wound care, the patient underwent a total of 49 sessions of HBOT at a pressure of 2.0 atmosphere absolutes, each for 90 minutes (including two air breaks). Allogenic stem cell transplantation was performed after the ninth treatment. The patient's complex sacral wound demonstrated markedly increased granulation in the early phase of HBOT, and after concurrent bone marrow transplantation it resolved completely by secondary intention. More than one year later it remained completely healed, and repeat bone marrow biopsy demonstrated a normocellular aspirate with stable circulating cell counts. CONCLUSION: Our report describes the novel advantages of HBOT over other conventional wound therapies in the context of severe haematologic compromise and supports its potential for synergy with bone marrow transplantation.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".