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Record W2085515548 · doi:10.1002/pbc.20757

Low prevalence of complications in severe neutropenic children with cancer in the unprotected environment of an overnight camp

2006· article· en· W2085515548 on OpenAlexaff
Uri Tabori, Heather Jones, David Malkin

Bibliographic record

VenuePediatric Blood & Cancer · 2006
Typearticle
Languageen
FieldMedicine
TopicNeutropenia and Cancer Infections
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsMedicineNeutropeniaBlood cancerCancerFebrile neutropeniaPediatricsChemotherapyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The high risk of infection and other complications in severely neutropenic pediatric oncology patients receiving chemotherapy has led to development of a variety of preventive measures including isolation and diet restrictions. In order to examine the potential impact of these measures, we evaluated the outcomes of such patients attending a recreational summer camp. METHODS: We collected data on all children who attended an overnight summer camp for children with cancer during the years 1999-2004, and who were either severely neutropenic or at a high-intensity phase of chemotherapy. Outcome measures included fever, bleeding, hospitalization, and clinical or laboratory evidence of infection. The observation period included both, the 2-week camp experience and 30 days post-camp. RESULTS: The study group was comprised of 34 patients. Although nine (24%) were hospitalized for management of fever and neutropenia, only one patient had clinical or culture-positive evidence of an invasive infectious agent. No bleeding episode was recorded and most patients attended all camp activities. CONCLUSIONS: Our results support the safety and feasibility of severely neutropenic patients with cancer to attend the non-isolated, non-sterile environment of a summer camp. These findings may be applicable to school and other social settings.

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 score0.006
Threshold uncertainty score0.994

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 head0.006
GPT teacher head0.236
Teacher spread0.229 · 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

Citations6
Published2006
Admission routes1
Has abstractyes

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