Management of antiretroviral therapy and opportunistic infections in people living with HIV undergoing hematopoietic stem cell transplant in British Columbia
Bibliographic record
Abstract
Background: A growing number of people living with HIV (PLWH) are developing an indication for hematopoietic stem cell transplantation (HSCT). While overlapping immunosuppression and medication interactions make this a complicated situation, the risk is mitigable, and PLWH should have similar access to HSCT as the general population. There are currently no guidelines available for the management of HSCT in PLWH, and through this document we hope to provide initial guidance. Methods: We performed a non-systematic review of published English-language literature regarding medication and opportunistic infection risk management in both PLWH and HSCT recipients, as well as local, national, and international guidelines. We then generated recommendations for PLWH undergoing HSCT that went through multiple rounds of review with the authors and expert peers. Results: Patients living with well-controlled HIV are expected to have similar outcomes with HSCT as people without HIV. Focus should be on minimizing interruptions in antiretroviral therapy, avoiding drug-drug interactions (minimized with integrase strand transfer inhibitors), and managing overlapping toxicities. Opportunistic infections common in both advanced HIV and in HSCT include Pneumocystis pneumonia, toxoplasmosis, herpes simplex virus, varicella zoster virus, and cytomegalovirus, with nontuberculous mycobacteria and cryptococcosis being somewhat more common in advanced HIV. Assuming a patient has well-controlled HIV, most of the opportunistic infection risk is due to transplant-related immunosuppression, and we provide specific prophylactic recommendations. Conclusions: PLWH should have similar access to HSCT as people without HIV, and we offer this document as guidance to support hematology/oncology providers.
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".