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Record W2440442001 · doi:10.1097/mbc.0000000000000395

Central venous access device insertion and perioperative management of patients with severe haemophilia A

2015· article· en· W2440442001 on OpenAlexaffabout
Adriana Fonseca, Kim Nagel, Kay Decker, Mimitha Pukulakatt, Mohan Pai, Mark E. Walton, Anthony K.C. Chan

Bibliographic record

VenueBlood Coagulation & Fibrinolysis · 2015
Typearticle
Languageen
FieldMedicine
TopicHemophilia Treatment and Research
Canadian institutionsMcMaster Children's HospitalHamilton Health SciencesMcMaster University
Fundersnot available
KeywordsMedicinePerioperativeHaemophiliaDosingHaemophilia BHaemophilia AVenous accessSurgeryPediatricsAnesthesiaInternal medicine

Abstract

fetched live from OpenAlex

Central venous access device (CVAD) insertion is one of the most common procedures performed on paediatric haemophilia patients. There are no clear guidelines outlining the optimal dosing schedule of factor VIII (FVIII) and duration of treatment required to achieve adequate haemostasis during and after surgery. In this article, we describe the experience at McMaster Children's Hospital using FVIII replacement therapy in 15 children with severe haemophilia A during the course of 7 years. This is a retrospective institutional chart review. Patients between 0 and 18 years of age with severe haemophilia A that underwent CVAD insertion at McMaster Children's Hospital in Hamilton, Ontario, from 2004 to 2010, were identified and charts were reviewed. A total of 15 CVAD insertion surgeries were reviewed. The total average preoperative dose of FVIII was 93.5 IU/kg (range: 53.7-145.4 IU/kg). The total average postoperative dose was 818.7 IU/kg (range: 441-1258 IU/kg). The total perioperative dose was 912.2 IU/kg (range: 495.2-1349 IU/kg). The current study attempts to describe the experience at McMaster Children's Hospital for CVAD insertion surgeries, the average factor dose administered has decreased during the years. These results may be of help in the development of optimal treatment schedules.

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 score0.011
Threshold uncertainty score0.407

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 head0.040
GPT teacher head0.294
Teacher spread0.254 · 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

Citations5
Published2015
Admission routes2
Has abstractyes

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