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High Prevalence of Peripheral Artery Occlusive Disease (PAOD) Among Patients with Chronic Myeloid Leukemia (CML) Receiving Tyrosine Kinase Inhibitors (TKIs): A Cross-Sectional Study

2015· article· en· W2560761889 on OpenAlexaff
Thanawat Rattanathammethee, Adisak Tantiworawit, Ekarat Rattarittamrong, Chatree Chai‐Adisaksopha, Sasinee Hantrakool, Arintaya Phrommintikul, Siriluck Gunaparn, Lalita Norasetthada

Bibliographic record

VenueBlood · 2015
Typearticle
Languageen
FieldMedicine
TopicChronic Myeloid Leukemia Treatments
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineNilotinibInternal medicineDasatinibDiabetes mellitusPopulationImatinibCoronary artery diseaseMyeloid leukemiaImatinib mesylateSurgeryGastroenterology

Abstract

fetched live from OpenAlex

Abstract Background: Although TKIs become the standard of care in CML, the long-term complication has not been well recognized. There were reports of nilotinib associated metabolic derangements including diabetes and PAOD while these complications in other TKIs have not been well recognized. Objectives: To compare the prevalence of PAOD among CML patients and matched-control population. Methods: A cross-sectional case control study was conducted among CML patients receiving TKIs at Chiang Mai University Hospital between February to December 2014. The control group was matched by age, sex and diabetes. Screening PAOD using Fukuda VS-1500 to measure ankle-brachial index (ABI) and cardio-ankle vascular index (CAVI) for arterial stiffness were performed in both groups. The cutoff value of pathologic ABI and CAVI were less than 0.9 and higher than 8, respectively. Results: Seventy-eight CML patients and 156 matched-control population(1:2 ratio) were included. For CML patients, the median age was 55 years (21-86). Atherosclerotic risks including hypertension(20.5%), diabetes(12.8%), dyslipidemia(26.9%), metabolic syndrome(19.2%) and smoking(2.6%). Sixty-one patients(78.2%) were on imatinib, all as first-line, 13 patients(16.7%) on nilotinib (7.7%first-line, 92.3%second-line) while 4 patients(5.2%) were on dasatinib(all third-line). Median duration of imatinib, nilotinib and dasatinib treatment were 89.6, 46.7 and 22.1 months, respectively. The prevalence of pathologic ABI and CAVI were 9.0% and 26.7%, respectively. Patients receiving nilotinib had highest prevalence of abnormal ABI of 30.7% while patients receiving imatinib and dasatinib had abnormal ABI of 5% and 0%, respectively (p=0.004). Abnormal arterial stiffness by CAVI in nilotinib users were 15.4% compared to 27.8% and 50% in imatinib and dasatinib (p=0.815). Patients with CML had higher prevalence of pathologic ABI than in control group with an odds ratio(OR) of 2.09(95%CI 0.71-6.21, p=0.181). The only factor independently associated with pathologic ABI was level of HbA1C over 7 g/dl [OR2.41(95%CI 1.11-5.25; p=0.026)]. Age over 60 years [OR 3.95(95%CI 1.22-12.73, p=0.022)] and fasting plasma glucose over 126 mg/dl [OR 7.96(95%CI 1.21-52.26, p=0.031)] were independently associated with pathologic CAVI. Conclusions: The prevalence of PAOD by using ABI was higher among CML patients than in control population. CML patients receiving TKIs who have diabetes and older than 60 years old have a higher chance of developing PAOD and should be carefully monitored. 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)0.001
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.011
GPT teacher head0.246
Teacher spread0.235 · 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
Published2015
Admission routes1
Has abstractyes

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