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Record W4214826031 · doi:10.1186/s13223-022-00662-6

Growth in diagnosis and treatment of primary immunodeficiency within the global Jeffrey Modell Centers Network

2022· article· en· W4214826031 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAllergy Asthma and Clinical Immunology · 2022
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmunodeficiency and Autoimmune Disorders
Canadian institutionsnot available
FundersInvitaeJeffrey Modell Foundation
KeywordsPrimary immunodeficiencyHuman immunodeficiency virus (HIV)Primary (astronomy)MedicineGerontologyVirologyInternal medicineDiseasePhysics

Abstract

fetched live from OpenAlex

BACKGROUND: Primary immunodeficiencies (PI), which include more than 450 single-gene inborn errors of immunity and may affect up to 1% of the population, are genetic disorders that impair the immune system. If not properly identified and treated, individuals with PI are subject to serious, prolonged, and sometimes life-threatening infections or autoimmunity. Despite advancements, awareness of PI remains a critical issue for physicians and the public alike, as this leads to the enhanced and expedited management of these conditions. To address this critical issue, the Jeffrey Modell Foundation (JMF) formed a global network of specialized centers. The goal of this endeavor was to raise awareness of PI to better identify, diagnose, and treat patients, reducing associated mortality and morbidity and improving quality of life (QOL). For more than two decades, the Jeffrey Modell Centers Network (JMCN) has served as the foundation upon which these goals have been pursued. The JMCN currently includes 909 Expert Physicians at 400 institutions, in 316 cities, and 86 countries spanning six continents. METHODS: A survey was developed by JMF for members of the JMCN, following the most recent Classification of PI from the IUIS Expert Committee, to periodically describe the patient population, including treatment modalities and demographics. Physician-reported data from 2021 was compared to that from 2018 and 2013. Physicians in the JMCN also reported on select outcomes of their PI patients one year prior to and one year following diagnosis. RESULTS: A total of 300 JMF Physician Surveys from 681 physicians were included in this analysis. This is a 75% physician response rate. From 2013 to 2021, there was a 96.3% increase in patients followed in the US and an 86.1% increase globally. During the same period, patients identified with a specific PI defect increased by 46.6% in the US and 47.9% globally. Patients receiving IgG and HSCT increased by 110% and 201% respectfully since 2013. Early diagnosis led to reported decreased morbidity and mortality and reduced calculated healthcare costs. CONCLUSIONS: This global analysis of physician-reported data on patients with PI demonstrates an increase in both diagnosed and treated patients. This substantial increase from within the JMCN is a testament to its impact. In addition to building an extensive global patient database, the expanding JMCN serves as a unique and critical resource, providing the infrastructure for earliest diagnosis, optimized treatments, and implementation of standard-of-care and best practices. The JMCN provides a critical platform that facilitates the education of physicians and patients, awareness initiatives, and research advances, through collaboration and connectivity, ultimately resulting in improved outcomes and QOL for patients with PI. The JMCN has steadily and substantially grown for more than two decades and continues to substantively impact the field of Immunology globally.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.465
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.017
GPT teacher head0.254
Teacher spread0.237 · 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