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Record W4406207207 · doi:10.7705/biomedica.7562

Características clínicas e inmunológicas de pacientes con déficit de anticuerpos específicos contra antígenos polisacáridos en un hospital pediátrico de Colombia

2024· article· es· W4406207207 on OpenAlexaff
Lina María Castaño‐Jaramillo, Alejandra Munevar, Andrea Carolina Marín, Milena Villamil‐Osorio, Sonia Restrepo‐Gualteros, Natalia Vélez‐Tirado

Bibliographic record

VenueBiomédica · 2024
Typearticle
Languagees
FieldImmunology and Microbiology
TopicImmunodeficiency and Autoimmune Disorders
Canadian institutionsMisericordia Community Hospital
Fundersnot available
KeywordsMedicine

Abstract

fetched live from OpenAlex

Introduction. Specific antibody deficiency is an innate error of humoral immunity characterized by normal levels of immunoglobulin isotypes, recurrent infections, and a reduced reaction to polysaccharide antigens in vaccines. Objective. To describe the clinical and immunological characteristics of patients with specific antibody deficiency attending a pediatric hospital in Bogotá between May 2021 and September 2023. Materials and methods. We reviewed the medical records of 16 patients with specific antibody deficiency. Results. The median age at diagnosis was six and a half years. Nine were male, and 7 had a history of prematurity. Eleven patients had adequate nutritional status, and 7 had standard height. The most frequent recurrent infection was pneumonia, affecting 12 patients; more than half of them experienced some associated complications. The most common phenotype was moderate, and 15 of the individuals received immunoglobulin as definitive treatment. Conclusion. Specific antibody deficiency is a frequently underdiagnosed functional alteration of the immune system. It should be suspected in patients experiencing recurrent otitis media and pneumonia or in cases complicated by septic shock, pleural effusion, or necrotizing pneumonia.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.004
GPT teacher head0.247
Teacher spread0.243 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations1
Published2024
Admission routes1
Has abstractyes

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