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P1542: COMORBIDITIES AND COMPLICATIONS ACROSS GENOTYPES IN ADULT PATIENTS WITH PYRUVATE KINASE DEFICIENCY: ANALYSIS FROM THE PEAK REGISTRY

2022· article· en· W4283734564 on OpenAlexaff
A Glenthøj, Rachael F. Grace, Eduard J. van Beers, Joan‐Lluís Vives Corrons, Bertil Glader, K. H. M. Kuo, C. Lander, Dagmar Pospı́šilová, Jean Williams, Y. Yan, Bryan McGee, Paola Bianchi

Bibliographic record

VenueHemaSphere · 2022
Typearticle
Languageen
FieldMedicine
TopicErythrocyte Function and Pathophysiology
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMissense mutationMedicinePyruvate kinase deficiencyGenotypeInternal medicinePediatricsCompound heterozygosityFrameshift mutationGastroenterologyPyruvate kinaseAlleleGeneticsMutationGeneBiologyGlycolysis

Abstract

fetched live from OpenAlex

Background: Pyruvate kinase (PK) deficiency is a rare, congenital, glycolytic enzymopathy caused by mutations in the PKLR gene, which leads to lifelong hemolytic anemia and may result in complications such as iron overload, pulmonary hypertension, and gallstones. PK deficiency has wide genetic heterogeneity, with >300 mutations reported, and previous data suggest that disease complications may be common regardless of genotype. Aims: To further characterize comorbidities/complications across genotypes in adult patients (pts) with PK deficiency enrolled in the Peak Registry (NCT03481738). Methods: The Peak Registry is a global retrospective and prospective observational study of adult and pediatric pts diagnosed with PK deficiency. For this analysis, adults (≥18 years [yrs]) with classifiable PKLR genotype data were grouped into 3 cohorts: missense/missense (M/M); missense/non-missense (M/NM); non-missense/non-missense (NM/NM). NM mutations include nonsense, frameshift, in-frame small indels, large deletions, and splicing variants (including R479H). Genotype classifications are aligned with those previously reported from the PK deficiency Natural History Study. Data on demographics, laboratory values, and medical history inclusive of comorbidities and complications were summarized descriptively. Results: As of 29Jun2021, 90 of 103 adult pts in the registry had classifiable PKLR genotype data; 57 (63.3%) were classified as M/M, 28 (31.1%) as M/NM, and 5 (5.6%) as NM/NM. Median age (range) of PK deficiency diagnosis was 21.0 yrs (0–68) for M/M pts, 12.0 yrs (0–40) for M/NM pts, and 0.0 yrs (0–0) for NM/NM pts (Table). Among the 87 pts with known transfusion status, 36.8% had never been transfused (M/M: 44.4%; M/NM: 28.6%; NM/NM: 0%). Splenectomy had been performed in almost half of M/M pts (47.3%), the majority of M/NM pts (60.7%), and all NM/NM pts (100%). At registry enrollment, median hemoglobin (range) in the M/M, M/NM, and NM/NM cohorts was 9.9 g/dL (7.1–14.2), 9.1 g/dL (6.7–14.1), and 7.3 g/dL (6.9–8.1), respectively. History of iron overload was observed in substantial numbers of pts, regardless of genotype; 40.0% in M/M pts, 46.4% in M/NM pts, and 60.0% in NM/NM pts. Of these pts, 25.0% of M/M pts and 12.5% of M/NM pts had a history of iron overload despite never having been transfused. Jaundice was common for pts across genotypes (M/M: 32.7%; M/NM: 44.4%; NM/NM: 25.0%). Other comorbidities/complications included biliary events (M/M: 30.4%; M/NM: 33.3%; NM/NM: 0%) and bone health problems (M/M: 23.2%; M/NM: 22.2%; NM/NM: 0%). Of 7 pts who experienced 13 thromboembolic events, timing of the events relative to splenectomy was known for 6 pts, and in all 6 pts, the thromboembolic events occurred after splenectomy. Overall, 41.1% of pts experienced ≥2 distinct comorbidities/complications, as defined in the Table (M/M: 38.6%; M/NM 50.0%; NM/NM 20.0%). Image:Summary/Conclusion: This analysis reveals that pts across all PKLR genotypes experienced a wide range of serious comorbidities/complications across multiple systems. In addition to the breadth of comorbidities presented, these data highlight the existence of multiple complications in individual pts with PK deficiency and the need for appropriate monitoring and management of these pts, regardless of genotype.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.642

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)0.0010.000

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 head0.013
GPT teacher head0.247
Teacher spread0.233 · 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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Citations0
Published2022
Admission routes1
Has abstractyes

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