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The Phenotypic Spectrum of Pyruvate Kinase Deficiency (PKD) from the PKD Natural History Study (NHS): Description of Four Severity Groups By Anemia Status

2015· article· en· W2560998810 on OpenAlexaffabout
Rachael F. Grace, D. Holmes Morton, Wilma Barcellini, Stefan Eber, Jenny M Depsotovic, Christine Knoll, Hassan M. Yaish, Peter E. Newburger, Jennifer Rothman, Alexis A. Thompson, Yaddanapudi Ravindranath, Joachim B. Kunz, Eduard J. van Beers, Marcin W. Włodarski, Kerri Nottage, Heng Wang, Mukta Sharma, Melissa J. Rose, Yves Pastore, Patricia J. Giardina, Melissa Rhodes, Kevin H.M. Kuo, Vicky R. Breakey, Ellis J. Neufeld, Dongjing Guo, Wendy B. London, Jill Falcone, Bertil Glader

Bibliographic record

VenueBlood · 2015
Typearticle
Languageen
FieldMedicine
TopicErythrocyte Function and Pathophysiology
Canadian institutionsMcMaster UniversityUniversity of TorontoUniversity Health NetworkCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsSplenectomyMedicineCohortAnemiaPediatricsInternal medicineSpleen

Abstract

fetched live from OpenAlex

Abstract Background: An international, multicenter registry was established to collect clinical data on patients with PKD, the most common glycolytic defect causing congenital non-spherocytic hemolytic anemia. Aim: To describe and categorize the phenotypic spectrum of PKD, including the range of lab parameters, management, and complications. Methods: 144 patients enrolled on the PKD NHS at 23 sites from 3/2014 to 6/2015. For this report, baseline and retrospective data were included. PKD patients were categorized into 4 severity groups (Gp1-Gp4), with increasing severity of the disease: Gp1. Never regularly transfused +/- prior acute transfusions; Gp2. Regular transfusions prior to splenectomy, post-splenectomy baseline hemoglobin (hb) >8.7 g/dl; Gp3. Regular transfusions prior to splenectomy, post-splenectomy baseline hb ≤8.7 g/dl; and Gp4. Post-splenectomy and currently regularly transfused. To reduce the risk of chance associations when dividing the cohort by phenotype, the cohort was divided into a test set (n=73) to define the categories and a subsequent validation set (n=71). Results: Median age at enrollment was 19.9 years (0.1-70.7) with 47% males. This cohort was 95% Caucasian and 38% Amish. Perinatal complications were frequently reported including preterm birth (33%), perinatal transfusions (35%), and hydrops (10%). Newborn jaundice was common, requiring phototherapy (91%) and/or exchange transfusion (46%). 68% (98/144) had undergone splenectomy at a median age of 3.1 years (0.6-28.1). Common indications for splenectomy included reducing transfusion burden, improving anemia, and enhancing quality of life. The median pre-splenectomy hb was 7.0 g/dl (4.5-12.5). Splenectomy reduced the transfusion burden in 91%. Triggers for hemolysis included: pregnancy (59%), infections (61%), stress (35%), and medications (6%). In the 37% (53/144) who required a cholecystectomy, the median age was 14 years (2.6-60.4) and 35 (66%) occurred post-splenectomy. In both the test and validation cohorts, increased severity was associated with a younger age at diagnosis (p<0.01) and higher ferritin (p<0.01, Table). More severe patients were more likely to receive iron chelation (p<0.01). Reticulocyte counts and MCV were incrementally higher with increasing severity in the non-regularly transfused Gps (p=0.02). Gp4 pts required regular transfusions even after splenectomy (11/98). In this group, the median age of splenectomy was 5.0 y (2.1-11.8). Ferritin was higher in those who had a splenectomy, even after adjusting for transfusion status (p<0.0001). In the Gp1 pts with available iron studies, even in the absence of regular transfusions, the majority had evidence of iron overload; 7/10 (70%) had a liver iron concentration (LIC) >4 mg/g dry weight and 9/11 (82%) had ferritin >500 ng/ml. Chelation was used in 35 patients at a median age of 11.8 years (1-53.7) with a median ferritin 815 ng/ml (182-5630) and median LIC 5.7 mg/g dry weight (1.7-46.0). Conclusions: This NHS cohort is the largest assembly of PKD patients to date. We defined 4 severity Groups, based on transfusion history, anemia, and splenectomy status. Complications (e.g. iron overload) correlate with disease severity but also occur in milder phenotypes. Based on these findings, regular monitoring of iron status and screening for gallstones should be considered. Transfusion dependence persisted despite splenectomy in 11% of patients. Prospective data from the NHS will provide guidance for monitoring and treatment in this rare anemia. Figure 1. Figure 1. Disclosures Grace: Agios: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Morton:Agios: Honoraria, Membership on an entity's Board of Directors or advisory committees. Eber:Agios: Honoraria, Membership on an entity's Board of Directors or advisory committees. Yaish:Agios: Membership on an entity's Board of Directors or advisory committees. Nottage:Janssen Pharmaceuticals: Employment. Kuo:Alexion: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis Canada: Honoraria, Membership on an entity's Board of Directors or advisory committees. Neufeld:Agios: Honoraria, Membership on an entity's Board of Directors or advisory committees.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.555
Threshold uncertainty score0.356

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 head0.030
GPT teacher head0.231
Teacher spread0.201 · 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 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".

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Citations2
Published2015
Admission routes2
Has abstractyes

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