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Transient hyperphosphatasemia in pediatric renal transplant patients – Is there a need for concern and when?

2010· article· en· W1528527567 on OpenAlexaff
Štěpán Kutílek, Sylva Skálová, Jennifer Vethamuthu, Pavel Geier

Bibliographic record

VenuePediatric Transplantation · 2010
Typearticle
Languageen
FieldMedicine
TopicBone health and treatments
Canadian institutionsChildren's Hospital of Eastern Ontario
Fundersnot available
KeywordsMedicineMetabolic bone diseaseDiseasePediatricsBone ageInternal medicineBone diseaseOsteoporosis

Abstract

fetched live from OpenAlex

Kutílek Š, Skálová S, Vethamuthu J, Geier P, Feber J. Transient hyperphosphatasemia in pediatric renal transplant patients – Is there a need for concern and when? Pediatr Transplantation 2012: 16: E5–E9. © 2010 John Wiley & Sons A/S. Abstract: TH of infancy and early childhood is characterized by transiently increased S‐ALP, predominantly its bone or liver isoforms. There are neither signs of metabolic bone disease or hepatopathy corresponding to the increased S‐ALP, nor a common underlying/triggering disease. TH may also occur in children post‐renal Tx, which may raise significant concerns and anxiety. We describe four patients aged 2.8–7 yr in whom the TH occurred at 11–34 (median = 28) months after Tx and lasted from 40 to 105 (median = 63) days. No obvious cause/trigger of TH could be found; the clinical status and bone turnover were not altered. In cases of TH post‐Tx, we recommend the evaluation of basic biochemical indices and wrist X‐ray. If these results are normal, TH is most likely the diagnosis and the S‐ALP can be monitored over the next three months without further testing. In patients with persisting TH for more than three months and/or in children with pre‐existing or suspected metabolic bone disease, further evaluation may be indicated. In conclusion, TH is a benign disorder in patients post‐Tx. Detailed investigation including bone biopsy is only indicated in patients with persisting TH.

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 score0.013
Threshold uncertainty score0.771

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 head0.012
GPT teacher head0.259
Teacher spread0.246 · 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".

Quick stats

Citations11
Published2010
Admission routes1
Has abstractyes

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