MétaCan
Menu
Back to cohort
Record W2997516778 · doi:10.1182/blood-2019-125352

Characterization of the Severe Phenotype of Pyruvate Kinase Deficiency

2019· article· en· W2997516778 on OpenAlexaffabout
Hanny Al‐Samkari, Eduard J. van Beers, D. Holmes Morton, Wilma Barcellini, Stefan Eber, Bertil Glader, Hassan M. Yaish, Satheesh Chonat, Kevin H.M. Kuo, Nina Kollmar, Jenny M. Despotovic, Dagmar Pospı́šilová, Christine Knoll, Janet L. Kwiatkowski, Yves Pastore, Alexis A. Thompson, Marcin W. Włodarski, Yaddanapudi Ravindranath, Jennifer Rothman, Heng Wang, Suzanne Holzhauer, Vicky R. Breakey, Madeleine Verhovsek, Joachim B. Kunz, Sujit Sheth, Mukta Sharma, Melissa J. Rose, Heather A. Bradeen, Melissa A. McNaull, Kathryn Addonizio, Hasan Al‐Sayegh, Wendy B. London, Rachael F. Grace

Bibliographic record

VenueBlood · 2019
Typearticle
Languageen
FieldMedicine
TopicErythrocyte Function and Pathophysiology
Canadian institutionsMcMaster UniversityMcMaster Children's HospitalUniversité de MontréalCentre Hospitalier Universitaire Sainte-JustineUniversity Health Network
Fundersnot available
KeywordsMedicineSplenectomyPyruvate kinase deficiencyAnemiaInternal medicineBlood transfusionHemolytic anemiaGastroenterologyPediatricsImmunologyPyruvate kinaseSpleen

Abstract

fetched live from OpenAlex

Background: Pyruvate kinase deficiency (PKD) is the most common cause of chronic hereditary non-spherocytic hemolytic anemia. The spectrum of disease in PKD is broad, ranging from an incidentally discovered mild anemia to a severe transfusion-dependent anemia. Splenectomy partially ameliorates the anemia and reduces the transfusion burden in the majority of patients. Because hemoglobin poorly correlates with symptoms in PKD, transfusion requirements are typically used clinically to classify disease severity with those who are regularly transfused despite splenectomy recognized as the most severely affected subgroup. Aim: To compare demographics, complications, and laboratory results between the most severely-affected PKD patients (those that are splenectomized and regularly transfused) with non-regularly transfused splenectomized PKD patients. Methods: After ethics committee approval, patients were enrolled on the PKD Natural History Study, a prospective 30 site international study. All patients had molecularly confirmed PKD. Only splenectomized patients were included in the analysis. Transfusion frequency was observed over a 3-year period. Patients were divided into two groups based on transfusion frequency: the severe phenotype group was defined as those who receive regular transfusions (≥6 discrete red cell transfusion episodes per year) and the control group did not receive regular transfusions. Phenotype stability over the 3-year period was also assessed. Results: 154 splenectomized patients with PKD were included: 30 patients in the severe PKD phenotype group and 124 patients in the comparison PKD group. Results of the analysis comparing the two groups are described in the Table. Severely affected patients were more likely to be female (77% versus 51%, p=0.013), older at the time of splenectomy (median age: 5 versus 3.6, p=0.011), have iron overload (93% vs. 51%, p<0.0001), have received chelation therapy (90% vs. 42%, p<0.0001), and had more lifetime transfusions (median: 77 versus 15, p<0.0001). Rates of other PKD complications including pulmonary hypertension, extramedullary hematopoiesis, liver cirrhosis, endocrinopathy, and bone fracture appear similar between the two groups. Laboratory values, including hemoglobin, total bilirubin, normalized PK enzyme activity, and median absolute reticulocyte count appear similar between the two groups. The underlying genetic mutation patterns (missense mutations versus non-missense mutations) were also similar between the groups. Phenotype stability over time was highly variable: of the patients with a severe phenotype at enrollment, 62% had a severe phenotype during the first follow-up year and 39% had a severe phenotype at the second follow-up year. Conclusions: Patients with PKD who are regularly transfused despite splenectomy appeared to have similar rates of PKD-associated complications (except for iron overload) and similar relevant laboratory values and genotypes when compared to those who are not regularly transfused after splenectomy. The similarity observed between severe phenotype patients and comparison patients with PKD may result from a protective effect of transfusion (e.g. reduction of bone fractures and extramedullary hematopoiesis) or could suggest transfusion-dependence is an artificial signifier of disease severity, reflective of provider practices and patient symptoms rather than an actual distinct phenotype. Transfusion requirements in severe PKD appear to fluctuate significantly over time. Disclosures Al-Samkari: Dova: Consultancy, Research Funding; Agios: Consultancy, Research Funding; Moderna: Consultancy. van Beers:RR Mechatronics: Research Funding; Agios Pharmaceuticals, Inc.: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Consultancy, Research Funding; Pfizer: Research Funding. Barcellini:Agios: Consultancy, Other: Advisory board; Apellis: Consultancy; Incyte: Consultancy, Other: Advisory board; Bioverativ: Consultancy, Other: Advisory board; Novartis: Research Funding, Speakers Bureau; Alexion: Consultancy, Research Funding, Speakers Bureau. Eber:Agios Pharmaceuticals, Inc.: Consultancy. Glader:Agios Pharmaceuticals, Inc: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Chonat:Alexion: Other: advisory board; Agios Pharmaceuticals, Inc.: Other: advisory board. Kuo:Pfizer: Consultancy; Novartis: Consultancy, Honoraria; Celgene: Consultancy; Agios: Consultancy; Alexion: Consultancy, Honoraria; Apellis: Consultancy; Bioverativ: Other: Data Safety Monitoring Board; Bluebird Bio: Consultancy. Despotovic:Dova: Honoraria; Novartis: Research Funding; Amgen: Research Funding. Kwiatkowski:Celgene: Consultancy; Terumo: Research Funding; Apopharma: Research Funding; bluebird bio, Inc.: Consultancy, Research Funding; Agios: Consultancy; Imara: Consultancy; Novartis: Research Funding. Thompson:Baxalta: Research Funding; Novartis: Consultancy, Research Funding; bluebird bio, Inc.: Consultancy, Research Funding; Celgene: Consultancy, Research Funding. Ravindranath:Agios Pharmaceuticals, Inc.: Other: I am site PI on several Agios-sponsored studies, Research Funding. Rothman:Pfizer: Consultancy, Honoraria, Research Funding; Novartis: Honoraria, Research Funding; Agios: Honoraria, Research Funding. Verhovsek:Sickle Cell Awareness Group of Ontario: Membership on an entity's Board of Directors or advisory committees; Sickle Cell Disease Association of Canada: Membership on an entity's Board of Directors or advisory committees, Research Funding; Canadian Haemoglobinopathy Association: Membership on an entity's Board of Directors or advisory committees; Vertex: Consultancy. Kunz:Novartis: Membership on an entity's Board of Directors or advisory committees. Sheth:CRSPR/Vertex: Other: Clinical Trial Steering committee; Apopharma: Other: Clinical trial DSMB; Celgene: Consultancy. London:United Therapeutics: Consultancy; ArQule, Inc: Consultancy. Grace:Novartis: Research Funding; Agios Pharmaceuticals, Inc: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding.

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 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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.543
Threshold uncertainty score0.303

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.009
GPT teacher head0.213
Teacher spread0.204 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueBloodSame topicErythrocyte Function and PathophysiologyFrench-language works237,207