A Systematic Review of Infectious Complications of Eculizumab
Bibliographic record
Abstract
Eculizumab, first-line therapy for paroxysmal nocturnal hemoglobinuria (PNH) and atypical hemolytic uremic syndrome (aHUS) has infectious side effects in addition to its therapeutic benefits. The mechanism of development of infections, treatment modalities and preventive strategies for the associated infections have been discussed in this systematic review. The study was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) checklist and reporting guidelines. Inclusion and exclusion criteria were determined. A total of 18 research papers were extracted after exploring the databases from 2001 to 2024. The New Castle Ottawa Questionnaire for non-randomized clinical trials and observational studies, the National Institutes of Health (NIH) quality assessment tool for case reports and case series, and the scale for the quality assessment of narrative review articles checklist for literature review were used to assess the risk of bias. The bacteria causing infection secondary to eculizumab are Neisseria meningitidis, Neisseria gonorrhoeae, unusual Neisseria species, Moraxella lacunata, and Pseudomonas aeruginosa and fungus causing infection secondary to eculizumab is Aspergillus niger. Health care providers should maintain a high index of suspicion for these adverse effects for early identification and treatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".