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Record W4409786563 · doi:10.70962/cis2025abstract.2

Post-Transplant Chronic Granulomatous Disease Patient Follow-Up: A PIDTC Survey

2025· article· en· W4409786563 on OpenAlexaff
Christin Deal, Anika Jain, Danielle E. Arnold, Suhag Parikh, Rebecca Marsh, Aleksandra Petrović, Kanwaldeep Mallhi, Deepak Chellapandian, Eyal Grunebaum, Emilia Liana Falcone, Luis Murguía-Favela, Elizabeth M. Kang, Harry L. Malech, Christopher C. Dvorak, Élie Haddad, Donald B. Kohn, Linda G. Griffith, Luigi D. Notarangelo, Michael A. Pulsipher, Alice Chan, Lauri Burroughs, Mort J. Cowan, Sung‐Yun Pai, Troy Torgerson, Jennifer M. Puck, Jennifer Heimall, Felicia B Morton, Jennifer W. Leiding

Bibliographic record

VenueJournal of Human Immunity · 2025
Typearticle
Languageen
FieldImmunology and Microbiology
TopicNeutrophil, Myeloperoxidase and Oxidative Mechanisms
Canadian institutionsUniversité de MontréalUniversity of CalgaryMontreal Clinical Research InstituteCentre Hospitalier Universitaire Sainte-JustineSickKids Foundation
Fundersnot available
KeywordsChronic granulomatous diseaseMedicineGranulomatous diseaseDiseaseDermatologyPathologyImmunology

Abstract

fetched live from OpenAlex

Background Chronic granulomatous disease (CGD) is an inborn error of immunity caused by defects in NADPH oxidase, which causes phagocyte dysfunction. CGD is characterized by recurrent infections and autoimmunity. Allogeneic hematopoietic stem cell transplantation (HSCT) is a curative therapy. However, data regarding patient satisfaction with post-HSCT state of health and quality of life are lacking. Methods A Primary Immune Deficiency Treatment Consortium (PIDTC) working group designed online surveys to assess post-HSCT quality of life and satisfaction with transplantation. Surveys were distributed from November 2023 to March 2024 to all members of the CGD Association of America (CGDAA). Adults who personally underwent or parents of children who underwent HSCT for CGD were asked to participate. Two surveys were offered: one for participants who were 18 years or older and one for parents of patients. Results Complete surveys representing 54 unique patients were included for analysis. Forty-four were from parents whose children were a median of 12 years old and a median of 6 years post-transplant. Nine were returned from patients who were a median of 30 years old and a median of 4 years post-transplant (Table 1). Table 1. Seventy-eight percent of patient and parent respondents reported that quality of life was better after transplant and 89% felt that the transplant improved their physical health (Figure 1). Figure 1. (A) Do you feel quality of life is better now post-transplant than it was pre-transplant? (B) Do you feel that the transplant has been beneficial from a medical perspective? PROMIS Global Health scoring tool revealed 84% of patients had mental health scores within 1 SE of the mean. Only a few mental health diagnoses were self-reported (Figure 2). Figure 2. (A) PROMIS Mental Health Report Scores. (B) Mental health condition diagnosed by a physician. After transplant, there were no self-reported cases of autoimmune disease or malignancy. Three participants were able to conceive children. One respondent used sperm banking; two did not use fertility preservation or treatments. Discussion Our data demonstrate that the majority of patients who undergo allogeneic HSCT for definitive treatment of CGD experience improvements in physical and/or mental health and enjoy an improved quality of life after transplant. Overall, this study supports positive outcomes for patients treated with allogeneic HSCT.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.014
GPT teacher head0.255
Teacher spread0.240 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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