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Record W1989794413 · doi:10.1002/pbc.10450

Factors influencing central line infections in children with acute lymphoblastic leukemia: Results of a single institutional study

2003· article· en· W1989794413 on OpenAlexaff
Adil Abbas, Christopher Fryer, C. Paltiel, Fares Chedid, Sami Felimban, Abdulmotalib A. Yousef, Taha Khattab

Bibliographic record

VenuePediatric Blood & Cancer · 2003
Typearticle
Languageen
FieldHealth Professions
TopicCentral Venous Catheters and Hemodialysis
Canadian institutionsBC Cancer AgencyBC Children's Hospital
Fundersnot available
KeywordsMedicineLymphoblastic LeukemiaCatheterCentral linePediatricsInfection rateLeukemiaPopulationSurgeryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: We compared the rates of infection in external catheters (ECs) and totally implantable devices (TIDs) and the effect of timing of insertion in children with acute lymphoblastic leukemia (ALL). PROCEDURE: Central line data was collected on all children with ALL referred to the National Guard Hospital, Jeddah. Data was collected retrospectively from 1996 to September 1999 and prospectively thereafter. Only ECs were inserted prior to 1999 subsequently TIDs were preferred. RESULTS: One hundred forty eight children with ALL, mean age 5.1 years had 129 ECs and 70 TIDs inserted for a total of 41,382 catheter days. The overall rate of infective episodes (infections/1,000 catheter days) was 3.43. Of the initial 148 lines 100 developed complications of which 76 (51%) were secondary to an infective episode. Only young age and treatment protocol were risk factors for first line infections (P < 0.05). There was weak evidence that ECs had an earlier time to infection compared to TIDs (P = 0.056). CONCLUSIONS: In this study, population central lines were associated with a high rate of infection. Treatment protocol and age were the only significant risk factors when only first lines were considered. Delaying catheter insertion for more than 3 weeks from diagnosis did not reduce the risk of infection.

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 score0.007
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.026
GPT teacher head0.304
Teacher spread0.278 · 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

Citations60
Published2003
Admission routes1
Has abstractyes

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