Infectious complications after autologous hematopoietic stem cell transplantation for patients with an autoimmune indication: A protocol for a systematic review and meta-analysis
Bibliographic record
Abstract
• With the growing number of aHSCT treatments performed for autoimmune diseases, gaining deeper insight into toxicities, particularly infectious complications, is essential. • Exploring infectious complications in patients undergoing aHSCT for autoimmune disease indications will enhance understanding of the infection spectrum and timing, in view of improving prophylaxis, early detection, and treatment strategies. • This systematic review will assess the robustness and quality of reporting on infectious complications. Inadequate data reporting would highlight the need for further research in the form of a prospective or retrospective registry-based study. Autologous hematopoietic stem cell transplantation (aHSCT) offers potential long-term remission for various autoimmune diseases, especially in patients unresponsive to conventional treatments. Notwithstanding its benefits, aHSCT carries risks from cytotoxic agents and temporary immunosuppression, leading to infectious complications. This systematic review focuses on the incidence and characteristics of infections in patients with autoimmune diseases undergoing aHSCT. Data will be collected from trials identified in a search across Medline, Embase, Cochrane Register of Controlled Trials, Web of Science, clinicaltrials.gov , and the International Clinical Trials Registry Platform. Eligible publications are any articles that include patients undergoing autologous hematopoietic stem cell transplantation where the primary indication is an autoimmune disease. Outcomes include infection characteristics, treatment-related and all-cause mortality, and the robustness and quality of infection reporting. Data screening, collection, and extraction will be conducted using Covidence. A narrative synthesis will describe the results, and meta-analysis will be performed if possible. This systematic review aims to define the risk of infections during and after stem cell transplantation for patients with autoimmune diseases the objective being to improve prophylaxis, early detection and treatment of infectious complications.
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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 | 0.049 | 0.077 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.020 | 0.033 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.047 | 0.005 |
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".