Dose adjustment of immunosuppressants during co-administration of posaconazole: a systematic review
Bibliographic record
Abstract
PURPOSE: The purpose of this retrospective study was to analyze the dose adjustment of immunosuppressants (cyclosporine, tacrolimus and sirolimus) for the patients with allogeneic hematopoietic stem cell and solid-organ (heart/lung) transplantation during co-administration of posaconazole. METHODS: MEDLINE, EMBASE and Cochrane Library were searched from January 1, 2000 to June 30, 2017 for clinical reports of patients who received allogeneic hematopoietic stem cell and organ transplantation and were co-administered posaconazole and immunosuppressants (cyclosporine, tacrolimus or sirolimus). RESULTS: Seven studies were included in the systematic review with a total of 215 patients. Five studies involved hematopoietic stem cell transplant, one heart transplant and one lung transplant. In general, the co-administration of posaconazole with sirolimus, tacrolimus or cyclosporine necessitated immunosuppressant dose reductions to maintain the levels of the drug in the optimal therapeutic range. Reported dose reductions were 50%-68% for sirolimus, 75% for tacrolimus and 14%-49% for cyclosporine. The findings were similar for hematopoietic stem cell, heart or lung transplantation studies. CONCLUSION: Our findings indicate that, when posaconazole is co-administered, the dosage of sirolimus and tacrolimus should be reduced by 60%-70% and for cyclosporine and by 30%-40% following allogeneic hematopoietic stem cell and solid-organ 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 | 0.006 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| 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".