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Record W2980682826 · doi:10.1182/blood-2018-99-119638

Mediastinal Mass, Triglycerides Level Above 1000mg/Dl and Intensive Dexamethasone and Asparaginase Treatment Are Risk Factors for Cerebral Sinus Venous Thrombosis in Children Treated for Acute Lymphoblastic Leukemia at the Children's Cancer Center of Lebanon

2018· article· en· W2980682826 on OpenAlexaff
Habib El‐Khoury, Khaled Ghanem, Yaacoub Mubarak, Nidale Tarek, Hassan El Solh, Anthony K.C. Chan, Carole Aridi, Miguel R. Abboud, Raya Saab, Samar Muwakkit

Bibliographic record

VenueBlood · 2018
Typearticle
Languageen
FieldMedicine
TopicAcute Lymphoblastic Leukemia research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineAsparaginaseDexamethasoneGastroenterologyInternal medicineAcute lymphocytic leukemiaOdds ratioVenous thrombosisRisk factorCumulative incidenceIncidence (geometry)PediatricsCohortSurgeryThrombosisLeukemiaLymphoblastic Leukemia

Abstract

fetched live from OpenAlex

Abstract Background: Cerebral sinus venous thrombosis (CSVT) is a serious complication of childhood acute lymphoblastic leukemia (ALL) therapy. No universal consensus exists regarding its risk factors due to rarity of cases. The effect of CSVT on outcome is not limited to its own complications but extends to its possible negative impact on ALL therapy. Age above 10 years, T-cell immunophenotype and risk stratification (intermediate/high risk) were previously shown to be statistically significant risk factors for CSVT in our cohort of patients with an odds ratio of 3.56, 2.32 and 3.40 respectively and a P-Value of 0.03, 0.02 and 0.04 respectively (Ghanem et al. 2017). Aims and Methods: This is a prospective study of a pediatric cohort of children between 1 and 18 years of age treated for Acute Lymphoblastic Leukemia at the Children's Cancer Center of Lebanon (CCCL) between 2007 and 2017 with a protocol adopted from St Jude TOT XV. The aim of this analysis is to study the effect of decreasing asparginase and dexamethasone doses on the incidence of CSVT in addition to studying the effect of the following potential risk factors: presence of mediastinal mass at diagnosis, triglycerides level above 1000mg/dL and elevated initial blast count. In 2015, L-asparginase doses were decreased during induction from 10,000IU/m2/dose to 6,000IU/m2/dose and Dexamethasone doses were decreased from 12mg/m2/dose to 8mg/m2/dose for intermediate/high risk patients and from 8mg/m2/dose to 6mg/m2/dose for low risk patients. Patients were divided into two groups: group I for individuals treated between 2007 and 2015 and group I for individuals treated between 2015 and 2017. Results: A total of 202 patients were recruited (Group I, N=126 and Group II, N=76). The incidence of CSVT was 10.3% in group I and 1.3 % in group II. Univariate analysis showed that, treatment with intensive dexamethasone and asparginase in group I was a significant risk factor for CSVT (OR: 9.3, 95% CI: 1.2 - 72, P=0.03). Initial mediastinal mass (OR: 19.3, 95% CI: 5.4 - 68.6, P<0.0001) and triglycerides level above 1000mg/dL (OR: 3.4, 95% CI: 0.98 - 12, P=0.05) were also associated with increased risk of CSVT. Initial peripheral blast count ≥10,000 (OR: 0.57, 95% CI: 0.19 - 1.7, P=0.31), ≥50,000 (OR: 0.7, 95% CI: 0.14-3.35, P=0.66), and ≥100,000 (OR: 1.53, 95% CI: 0.29-7.82, P=0.61) were not risk factors for CSVT in our cohort. Conclusion: Decreasing the doses of dexamethasone and asparginase significantly lowered the risk of CSVT in our patient population. Initial mediatinal mass and triglycerides levels above 1000mg/dL during asaparginase therapy were significantly associated with increased risk of developing CSVT. If future studies confirm our findings, mediastinal mass and elevated triglycerides level may be considered amongst other factors predisposing to CSVT and may help identify candidates for thromboprophylaxis in the future. Disclosures No relevant conflicts of interest to declare.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.025
GPT teacher head0.294
Teacher spread0.269 · 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 source (direct Gemma or distilled Codex), 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
Published2018
Admission routes1
Has abstractyes

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