<p>Epidemiology of Atypical Hemolytic Uremic Syndrome: A Systematic Literature Review</p>
Bibliographic record
Abstract
Atypical hemolytic uremic syndrome (aHUS) is a rare but severe disorder that frequently has a genetic component and results from the overactivation of the alternative complement pathway. As research moves toward improved diagnosis and therapy of aHUS, it will be important to better understand its epidemiology. Our objective was to conduct a systematic literature review to assess the incidence and prevalence estimates of aHUS globally. A comprehensive literature search was conducted in Embase and MEDLINE. Additionally, practice guidelines, databases of national/international organizations, and regulatory agencies were searched. From 2960 publications identified via MEDLINE and Embase, 105 publications were eligible for full-text screening, and a total of eight full-text articles met eligibility criteria for inclusion. Regional epidemiologic estimates were obtained for Europe and Oceania. Country-specific data were available for France, Norway, Australia, and Italy. Four of the identified studies reported on the prevalence of aHUS, prevalence in the age group of 20 years or younger was ranging from 2.2 to 9.4 per million population, while the only study that reported prevalence in all ages showed a prevalence of 4.9 per million population. Six studies reported on the incidence of aHUS, annual incidence in the age group of 20 years or younger was ranging from 0.26 to 0.75 per million population, and for all ages, annual incidence was ranging from 0.23 to 1.9 per million population. To our knowledge, this is the first systematic review conducted to provide a comprehensive overview of global incidence and prevalence estimates of aHUS. In general, incidence estimates were similar across all the studies; however, prevalence data were found to be more variable. Study limitations were related to inconsistencies in the definitions of aHUS between studies and also a dearth of epidemiological studies assessing incidence and prevalence of aHUS outside of Europe.
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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 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.017 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".