MétaCan
Menu
Back to cohort
Record W3159448849 · doi:10.14740/jh820

Autoimmune Hemolytic Anemia Associated With Human Babesiosis

2021· review· en· W3159448849 on OpenAlexvenueno aff
Pramuditha Rajapakse, Kamila Bakirhan

Bibliographic record

VenueJournal of Hematology · 2021
Typereview
Languageen
FieldMedicine
TopicBlood groups and transfusion
Canadian institutionsnot available
Fundersnot available
KeywordsBabesiosisAutoimmune hemolytic anemiaMedicineImmunologyAnemiaEquine infectious anemiaHemolytic anemiaVirologyAntibodyInternal medicine

Abstract

fetched live from OpenAlex

Babesiosis is characterized by non-autoimmune hemolytic anemia as a result of invasion of red blood cells by intraerythrocytic protozoans. Upon evaluation of patients who have ongoing hemolysis despite antibiotic treatment, a new entity of autoimmune hemolytic anemia (AIHA) was recently identified in some patients with babesiosis. The data are limited to case reports and one case series. The aim of this research was to synthetize data on this topic according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines using the PubMed database. In this review, we found that all patients who had developed AIHA were asplenic. All had Coombs test positive for IgG or both IgG and C3 indicating Warm AIHA. Some but not all required blood transfusion and plasma exchange. Majority of patients responded to steroids and had resolution of parasitemia on follow-up. We believe that this review will make the clinicians aware that babesiosis can not only cause non-immune hemolysis but also AIHA. It is important to differentiate between the two entities as antibiotics alone may not be sufficient for immune-mediated hemolysis caused by babesiosis.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0030.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.036
GPT teacher head0.331
Teacher spread0.295 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations16
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of HematologySame topicBlood groups and transfusionFrench-language works237,207